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Volumn 30, Issue , 2012, Pages 351-413

Locally Stationary Processes

Author keywords

Derivative process; Empirical spectral process; Local likelihood; Locally stationary process; Shape curve; Time varying autoregressive process; Time varying parameter; Time varying spectral density

Indexed keywords


EID: 84861367503     PISSN: 01697161     EISSN: None     Source Type: Book Series    
DOI: 10.1016/B978-0-444-53858-1.00013-2     Document Type: Chapter
Times cited : (186)

References (132)
  • 2
    • 78651246859 scopus 로고    scopus 로고
    • Local likelihood estimation for nonstationary random fields
    • Anderes E.B., Stein M.L. Local likelihood estimation for nonstationary random fields. J. Multivar. Anal. 2011, 102:506-520.
    • (2011) J. Multivar. Anal. , vol.102 , pp. 506-520
    • Anderes, E.B.1    Stein, M.L.2
  • 4
    • 56949084319 scopus 로고    scopus 로고
    • On parameter estimation for locally stationary long-memory processes
    • Beran J. On parameter estimation for locally stationary long-memory processes. J. Stat. Plann. Inference 2009, 139:900-915.
    • (2009) J. Stat. Plann. Inference , vol.139 , pp. 900-915
    • Beran, J.1
  • 5
    • 1842441339 scopus 로고    scopus 로고
    • GARCH processes: structure and estimation
    • Berkes I., Horváth L., Kokoskza P. GARCH processes: structure and estimation. Bernoulli 2003, 9:201-207.
    • (2003) Bernoulli , vol.9 , pp. 201-207
    • Berkes, I.1    Horváth, L.2    Kokoskza, P.3
  • 8
    • 84861392828 scopus 로고    scopus 로고
    • Costationarity of locally stationary time series
    • Article 1, doi:10.2202/1941-1928.1074
    • Cardinali A., Nason G. Costationarity of locally stationary time series. J. Time Ser. Econom. 2010, 2(2). Article 1. doi:10.2202/1941-1928.1074.
    • (2010) J. Time Ser. Econom. , vol.2 , Issue.2
    • Cardinali, A.1    Nason, G.2
  • 9
    • 77958452933 scopus 로고    scopus 로고
    • Order selection for heteroscedastic autoregression: A study on concentration
    • Chandler G. Order selection for heteroscedastic autoregression: A study on concentration. Stat. Prob. Lett. 2010, 80:1904-1910.
    • (2010) Stat. Prob. Lett. , vol.80 , pp. 1904-1910
    • Chandler, G.1
  • 10
    • 33645524962 scopus 로고    scopus 로고
    • Discrimination of locally stationary time series based on the excess mass functional
    • Chandler G., Polonik W. Discrimination of locally stationary time series based on the excess mass functional. J. Am. Stat. Assoc. 2006, 101:240-253.
    • (2006) J. Am. Stat. Assoc. , vol.101 , pp. 240-253
    • Chandler, G.1    Polonik, W.2
  • 12
    • 16244387347 scopus 로고    scopus 로고
    • Time-domain estimation of time-varying linear systems
    • Chiann C., Morettin P. Time-domain estimation of time-varying linear systems. J. Nonpar. Stat. 2005, 17:365-383.
    • (2005) J. Nonpar. Stat. , vol.17 , pp. 365-383
    • Chiann, C.1    Morettin, P.2
  • 13
    • 38249029345 scopus 로고
    • Empirical spectral processes and their applications to time series analysis
    • Dahlhaus R. Empirical spectral processes and their applications to time series analysis. Stoch. Proc. Appl. 1988, 30:69-83.
    • (1988) Stoch. Proc. Appl. , vol.30 , pp. 69-83
    • Dahlhaus, R.1
  • 14
    • 0030095346 scopus 로고    scopus 로고
    • On the Kullback-Leibler information divergence for locally stationary processes
    • Dahlhaus R. On the Kullback-Leibler information divergence for locally stationary processes. Stoch. Proc. Appl. 1996, 62:139-168.
    • (1996) Stoch. Proc. Appl. , vol.62 , pp. 139-168
    • Dahlhaus, R.1
  • 15
    • 0011460348 scopus 로고    scopus 로고
    • Maximum likelihood estimation and model selection for locally stationary processes
    • Dahlhaus R. Maximum likelihood estimation and model selection for locally stationary processes. J. Nonpar. Stat. 1996, 6:171-191.
    • (1996) J. Nonpar. Stat. , vol.6 , pp. 171-191
    • Dahlhaus, R.1
  • 16
    • 0003260218 scopus 로고    scopus 로고
    • Asymptotic statistical inference for nonstationary processes with evolutionary spectra
    • Springer, New York, P.M. Robinson, M. Rosenblatt (Eds.)
    • Dahlhaus R. Asymptotic statistical inference for nonstationary processes with evolutionary spectra. Athens Conference on Applied Probability and Time Series, Vol II. Lecture Notes in Statistics 1996, Vol. 115:145-159. Springer, New York. P.M. Robinson, M. Rosenblatt (Eds.).
    • (1996) Athens Conference on Applied Probability and Time Series, Vol II. Lecture Notes in Statistics , vol.115 , pp. 145-159
    • Dahlhaus, R.1
  • 17
    • 0031518090 scopus 로고    scopus 로고
    • Fitting time series models to nonstationary processes
    • Dahlhaus R. Fitting time series models to nonstationary processes. Ann. Stat. 1997, 25:1-37.
    • (1997) Ann. Stat. , vol.25 , pp. 1-37
    • Dahlhaus, R.1
  • 18
    • 0034343455 scopus 로고    scopus 로고
    • A likelihood approximation for locally stationary processes
    • Dahlhaus R. A likelihood approximation for locally stationary processes. Ann. Stat. 2000, 28:1762-1794.
    • (2000) Ann. Stat. , vol.28 , pp. 1762-1794
    • Dahlhaus, R.1
  • 19
    • 67650726879 scopus 로고    scopus 로고
    • Local inference for locally stationary time series based on the empirical spectral measure
    • Dahlhaus R. Local inference for locally stationary time series based on the empirical spectral measure. J. Econom. 2009, 151:101-112.
    • (2009) J. Econom. , vol.151 , pp. 101-112
    • Dahlhaus, R.1
  • 20
    • 0001329087 scopus 로고    scopus 로고
    • On the optimal segment length for parameter estimates for locally stationary time series
    • Dahlhaus R., Giraitis L. On the optimal segment length for parameter estimates for locally stationary time series. J. Time Ser. Anal. 1998, 19:629-655.
    • (1998) J. Time Ser. Anal. , vol.19 , pp. 629-655
    • Dahlhaus, R.1    Giraitis, L.2
  • 21
    • 0042409321 scopus 로고    scopus 로고
    • Locally adaptive fitting of semiparametric models to nonstationary time series
    • Dahlhaus R., Neumann M.H. Locally adaptive fitting of semiparametric models to nonstationary time series. Stoch. Proc. and Appl. 2001, 91:277-308.
    • (2001) Stoch. Proc. and Appl. , vol.91 , pp. 277-308
    • Dahlhaus, R.1    Neumann, M.H.2
  • 22
    • 0011243724 scopus 로고    scopus 로고
    • Nonlinear wavelet estimation of time-varying autoregressive processes
    • Dahlhaus R., Neumann M.H., von Sachs R. Nonlinear wavelet estimation of time-varying autoregressive processes. Bernoulli 1999, 5:873-906.
    • (1999) Bernoulli , vol.5 , pp. 873-906
    • Dahlhaus, R.1    Neumann, M.H.2    von Sachs, R.3
  • 23
    • 33746204150 scopus 로고    scopus 로고
    • Nonparametric quasi maximum likelihood estimation for Gaussian locally stationary processes
    • Dahlhaus R., Polonik W. Nonparametric quasi maximum likelihood estimation for Gaussian locally stationary processes. Ann. Stat. 2006, 34:2790-2824.
    • (2006) Ann. Stat. , vol.34 , pp. 2790-2824
    • Dahlhaus, R.1    Polonik, W.2
  • 24
    • 62749171757 scopus 로고    scopus 로고
    • Empirical spectral processes for locally stationary time series
    • Dahlhaus R., Polonik W. Empirical spectral processes for locally stationary time series. Bernoulli 2009, 15:1-39.
    • (2009) Bernoulli , vol.15 , pp. 1-39
    • Dahlhaus, R.1    Polonik, W.2
  • 25
    • 33747154976 scopus 로고    scopus 로고
    • Statistical inference for locally stationary ARCH models
    • Dahlhaus R., Subba Rao S. Statistical inference for locally stationary ARCH models. Ann. Stat. 2006, 34:1075-1114.
    • (2006) Ann. Stat. , vol.34 , pp. 1075-1114
    • Dahlhaus, R.1    Subba Rao, S.2
  • 26
    • 37549031844 scopus 로고    scopus 로고
    • A recursive online algorithm for the estimation of time-varying ARCH parameters
    • Dahlhaus R., Subba Rao S. A recursive online algorithm for the estimation of time-varying ARCH parameters. Bernoulli 2007, 13:389-422.
    • (2007) Bernoulli , vol.13 , pp. 389-422
    • Dahlhaus, R.1    Subba Rao, S.2
  • 27
    • 33645513464 scopus 로고    scopus 로고
    • Structural break estimation for nonstationary time series models
    • Davis R.A., Lee T., Rodriguez-Yam G. Structural break estimation for nonstationary time series models. J. Am. Stat. Assoc. 2005, 101:223-239.
    • (2005) J. Am. Stat. Assoc. , vol.101 , pp. 223-239
    • Davis, R.A.1    Lee, T.2    Rodriguez-Yam, G.3
  • 28
    • 49549085281 scopus 로고    scopus 로고
    • Break detection for a class of nonlinear time series models
    • Davis R.A., Lee T., Rodriguez-Yam G. Break detection for a class of nonlinear time series models. J. Time Ser. Anal. 2008, 29:834-867.
    • (2008) J. Time Ser. Anal. , vol.29 , pp. 834-867
    • Davis, R.A.1    Lee, T.2    Rodriguez-Yam, G.3
  • 29
    • 39749203615 scopus 로고    scopus 로고
    • Locally stationary processes and the local bootstrap
    • Elsevier Science B.V., Amsterdam, M.G. Akritas, D.N. Politis (Eds.)
    • Dowla A., Paparoditis E., Politis D.N. Locally stationary processes and the local bootstrap. Recent Advances and Trends in Nonparametric Statistics 2003, 437-445. Elsevier Science B.V., Amsterdam. M.G. Akritas, D.N. Politis (Eds.).
    • (2003) Recent Advances and Trends in Nonparametric Statistics , pp. 437-445
    • Dowla, A.1    Paparoditis, E.2    Politis, D.N.3
  • 30
    • 64849095956 scopus 로고    scopus 로고
    • Quantile curve estimation and visualization for non-stationary time series
    • Draghicescu D., Guillas S., Wu W.B. Quantile curve estimation and visualization for non-stationary time series. J. Comput. Graph. Stat. 2009, 18:1-20.
    • (2009) J. Comput. Graph. Stat. , vol.18 , pp. 1-20
    • Draghicescu, D.1    Guillas, S.2    Wu, W.B.3
  • 31
    • 0001027921 scopus 로고
    • A central limit theorem for parameter estimation in stationary vector time series and its application to models for a signal observed with noise
    • Dunsmuir W. A central limit theorem for parameter estimation in stationary vector time series and its application to models for a signal observed with noise. Ann. Stat. 1979, 7:490-506.
    • (1979) Ann. Stat. , vol.7 , pp. 490-506
    • Dunsmuir, W.1
  • 32
    • 78650069723 scopus 로고    scopus 로고
    • A test for second-order stationarity of a time series based on the discrete Fourier transform
    • Dwivedi Y., Subba Rao S. A test for second-order stationarity of a time series based on the discrete Fourier transform. J. Time Ser. Anal. 2011, 32:68-91.
    • (2011) J. Time Ser. Anal. , vol.32 , pp. 68-91
    • Dwivedi, Y.1    Subba Rao, S.2
  • 33
    • 0002014478 scopus 로고
    • On methods for obtaining asymptotically efficient spectral parameter estimates for a stationary Gaussian process with rational spectral density
    • Dzhaparidze K. On methods for obtaining asymptotically efficient spectral parameter estimates for a stationary Gaussian process with rational spectral density. Theory Probab. Appl. 1971, 16:550-554.
    • (1971) Theory Probab. Appl. , vol.16 , pp. 550-554
    • Dzhaparidze, K.1
  • 35
    • 77955077229 scopus 로고    scopus 로고
    • Locally stationary wavelet fields with application to the modelling and analysis of image texture
    • Eckley I.A., Nason G.P., Treloar R.L. Locally stationary wavelet fields with application to the modelling and analysis of image texture. Appl. Statist. 2010, 59:595-616.
    • (2010) Appl. Statist. , vol.59 , pp. 595-616
    • Eckley, I.A.1    Nason, G.P.2    Treloar, R.L.3
  • 36
    • 79956362468 scopus 로고    scopus 로고
    • Fitting dynamic factor models to non-stationary time series
    • Eichler M., Motta G., von Sachs R. Fitting dynamic factor models to non-stationary time series. J. Econom. 2011, 163:51-70.
    • (2011) J. Econom. , vol.163 , pp. 51-70
    • Eichler, M.1    Motta, G.2    von Sachs, R.3
  • 37
    • 0012895916 scopus 로고    scopus 로고
    • The periodogram of an i.i.d. sequence
    • Fay G., Soulier P. The periodogram of an i.i.d. sequence. Stoch. Proc. Appl. 2001, 92:315-343.
    • (2001) Stoch. Proc. Appl. , vol.92 , pp. 315-343
    • Fay, G.1    Soulier, P.2
  • 38
    • 0002188727 scopus 로고
    • Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series
    • Fox R., Taqqu M.S. Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series. Ann. Stat. 1986, 14:517-532.
    • (1986) Ann. Stat. , vol.14 , pp. 517-532
    • Fox, R.1    Taqqu, M.S.2
  • 39
    • 23044507598 scopus 로고    scopus 로고
    • Modelling and forecasting financial log-returns as locally stationary wavelet processes
    • Fryzlewicz P. Modelling and forecasting financial log-returns as locally stationary wavelet processes. J. Appl. Stat. 2005, 32:503-528.
    • (2005) J. Appl. Stat. , vol.32 , pp. 503-528
    • Fryzlewicz, P.1
  • 40
    • 33746216309 scopus 로고    scopus 로고
    • Haar-Fisz estimation of evolutionary wavelet spectra
    • Fryzlewicz P., Nason G.P. Haar-Fisz estimation of evolutionary wavelet spectra. J. R. Stat. Soc. B 2006, 68:611-634.
    • (2006) J. R. Stat. Soc. B , vol.68 , pp. 611-634
    • Fryzlewicz, P.1    Nason, G.P.2
  • 41
    • 70350342035 scopus 로고    scopus 로고
    • Consistent classification of nonstationary time series using stochastic wavelet representations
    • Fryzlewicz P., Ombao H. Consistent classification of nonstationary time series using stochastic wavelet representations. J. Am. Stat. Assoc. 2009, 104:299-312.
    • (2009) J. Am. Stat. Assoc. , vol.104 , pp. 299-312
    • Fryzlewicz, P.1    Ombao, H.2
  • 42
    • 33746247613 scopus 로고    scopus 로고
    • A Haar-Fisz technique for locally stationary volatility estimation
    • Fryzlewicz P., Sapatinas T., Subba Rao S. A Haar-Fisz technique for locally stationary volatility estimation. Biometrika 2006, 93:687-704.
    • (2006) Biometrika , vol.93 , pp. 687-704
    • Fryzlewicz, P.1    Sapatinas, T.2    Subba Rao, S.3
  • 43
    • 51049101671 scopus 로고    scopus 로고
    • Normalised least-squares estimation in time-varying ARCH models
    • Fryzlewicz P., Sapatinas T., Subba Rao S. Normalised least-squares estimation in time-varying ARCH models. Ann. Stat. 2008, 36:742-786.
    • (2008) Ann. Stat. , vol.36 , pp. 742-786
    • Fryzlewicz, P.1    Sapatinas, T.2    Subba Rao, S.3
  • 44
    • 79951650717 scopus 로고    scopus 로고
    • On mixing properties of ARCH and time-varying ARCH processes
    • Fryzlewicz P., Subba Rao S. On mixing properties of ARCH and time-varying ARCH processes. Bernoulli 2011, 17:320-346.
    • (2011) Bernoulli , vol.17 , pp. 320-346
    • Fryzlewicz, P.1    Subba Rao, S.2
  • 45
    • 11144355355 scopus 로고    scopus 로고
    • Forecasting non-stationary time series by wavelet process modeling
    • Fryzlewicz P., Van Bellegem S., von Sachs R. Forecasting non-stationary time series by wavelet process modeling. Ann. Inst. Stat. Math. 2003, 55:737-764.
    • (2003) Ann. Inst. Stat. Math. , vol.55 , pp. 737-764
    • Fryzlewicz, P.1    Van Bellegem, S.2    von Sachs, R.3
  • 46
    • 0034897555 scopus 로고    scopus 로고
    • A high frequency kriging approach for non-stationary environmental processes
    • Fuentes M. A high frequency kriging approach for non-stationary environmental processes. Environmetrics 2001, 12:469-483.
    • (2001) Environmetrics , vol.12 , pp. 469-483
    • Fuentes, M.1
  • 47
    • 33746395956 scopus 로고
    • Testing and estimating in the change-point problem of the spectral function
    • Giraitis L., Leipus R. Testing and estimating in the change-point problem of the spectral function. Lith. Math. J. 1992, 32:15-29.
    • (1992) Lith. Math. J. , vol.32 , pp. 15-29
    • Giraitis, L.1    Leipus, R.2
  • 50
    • 0020798029 scopus 로고
    • Time dependent ARMA modelling of nonstationary signals
    • Grenier Y. Time dependent ARMA modelling of nonstationary signals. IEEE Trans. Acoust. Speech Signal Process 1983, 31:899-911.
    • (1983) IEEE Trans. Acoust. Speech Signal Process , vol.31 , pp. 899-911
    • Grenier, Y.1
  • 52
    • 0242595638 scopus 로고    scopus 로고
    • Smoothing spline ANOVA for time-dependent spectral analysis
    • Guo W., Dai M., Ombao H.C., von Sachs R. Smoothing spline ANOVA for time-dependent spectral analysis. J. Am. Stat. Assoc. 2003, 98:643-652.
    • (2003) J. Am. Stat. Assoc. , vol.98 , pp. 643-652
    • Guo, W.1    Dai, M.2    Ombao, H.C.3    von Sachs, R.4
  • 53
    • 0000302722 scopus 로고
    • The asymptotic theory of linear time series models
    • Hannan E.J. The asymptotic theory of linear time series models. J. Appl. Prob. 1973, 10:130-145.
    • (1973) J. Appl. Prob. , vol.10 , pp. 130-145
    • Hannan, E.J.1
  • 54
    • 0001437332 scopus 로고
    • Nonstationary q-dependent processes and time-varying moving average models: invertibility properties and the forecasting problem
    • Hallin M. Nonstationary q-dependent processes and time-varying moving average models: invertibility properties and the forecasting problem. Adv. Appl. Probab. 1986, 18:170-210.
    • (1986) Adv. Appl. Probab. , vol.18 , pp. 170-210
    • Hallin, M.1
  • 55
    • 84861351523 scopus 로고    scopus 로고
    • Discriminant analysis for multivariate non-Gaussian locally stationary processes
    • Hirukawa J. Discriminant analysis for multivariate non-Gaussian locally stationary processes. Sci. Math. Japonicae Online 2004, 10:235-258.
    • (2004) Sci. Math. Japonicae Online , vol.10 , pp. 235-258
    • Hirukawa, J.1
  • 56
    • 32644443607 scopus 로고    scopus 로고
    • Cluster analysis for non-Gaussian locally stationary processes
    • Hirukawa J. Cluster analysis for non-Gaussian locally stationary processes. Int. J. Theor. Appl. Fin. 2006, 9:113-132.
    • (2006) Int. J. Theor. Appl. Fin. , vol.9 , pp. 113-132
    • Hirukawa, J.1
  • 57
    • 84861411726 scopus 로고    scopus 로고
    • Generalized information criteria in model selection for locally stationary processes
    • Hirukawa J., Kato H.S., Tamaki K., Taniguchi M. Generalized information criteria in model selection for locally stationary processes. J. Japan Stat. Soc. 2008, 38:157-171.
    • (2008) J. Japan Stat. Soc. , vol.38 , pp. 157-171
    • Hirukawa, J.1    Kato, H.S.2    Tamaki, K.3    Taniguchi, M.4
  • 58
    • 28044449583 scopus 로고    scopus 로고
    • LAN theorem for non-Gaussian locally stationary processes and its applications
    • Hirukawa J., Taniguchi M. LAN theorem for non-Gaussian locally stationary processes and its applications. J. Stat. Plan. Infer. 2006, 136:640-688.
    • (2006) J. Stat. Plan. Infer. , vol.136 , pp. 640-688
    • Hirukawa, J.1    Taniguchi, M.2
  • 59
    • 0000963884 scopus 로고
    • A central limit theorem for stationary processes and the parameter estimation of linear processes
    • Hosoya Y., Taniguchi M. A central limit theorem for stationary processes and the parameter estimation of linear processes. Ann. Stat. 1982, 10:132-153.
    • (1982) Ann. Stat. , vol.10 , pp. 132-153
    • Hosoya, Y.1    Taniguchi, M.2
  • 60
    • 4944222924 scopus 로고    scopus 로고
    • Discrimination and Classification of Nonstationary Time Series Using the SLEX Model
    • Huang H.-Y., Ombao H.C., Stoffer D.S. Discrimination and Classification of Nonstationary Time Series Using the SLEX Model. J. Amer. Stat. Assoc. 2004, 99:763-774.
    • (2004) J. Amer. Stat. Assoc. , vol.99 , pp. 763-774
    • Huang, H.-Y.1    Ombao, H.C.2    Stoffer, D.S.3
  • 61
    • 84861392829 scopus 로고    scopus 로고
    • Asymptotik eines nicht-parametrischen Kernschätzers für zeitvariable autoregressive Prozesse. Diploma thesis, University of Braunschweig.
    • Jentsch, C., 2006. Asymptotik eines nicht-parametrischen Kernschätzers für zeitvariable autoregressive Prozesse. Diploma thesis, University of Braunschweig.
    • (2006)
    • Jentsch, C.1
  • 63
    • 84861392831 scopus 로고    scopus 로고
    • Nonparametric kernel estimation of evolutionary autoregressive processes. Discussion paper 103. Sonderforschungsbereich 373, Berlin.
    • Kim, W., 2001. Nonparametric kernel estimation of evolutionary autoregressive processes. Discussion paper 103. Sonderforschungsbereich 373, Berlin.
    • (2001)
    • Kim, W.1
  • 64
    • 51249186419 scopus 로고
    • A Procedure for The Modeling of Non-Stationary Time Series
    • Kitagawa G., Akaike H. A Procedure for The Modeling of Non-Stationary Time Series. Ann. Inst. Stat. Math. 1978, 30 B:351-363.
    • (1978) Ann. Inst. Stat. Math. , vol.30 B , pp. 351-363
    • Kitagawa, G.1    Akaike, H.2
  • 65
    • 0021819062 scopus 로고
    • A smoothness priors time-varying AR coefficient modeling of the nonstationary covariance time series
    • Kitagawa G., Gersch W. A smoothness priors time-varying AR coefficient modeling of the nonstationary covariance time series. IEEE Trans. Automat. Cntrl. 1985, 30:48-56.
    • (1985) IEEE Trans. Automat. Cntrl. , vol.30 , pp. 48-56
    • Kitagawa, G.1    Gersch, W.2
  • 66
    • 84861406667 scopus 로고    scopus 로고
    • Semiparametric estimation of locally stationary diffusion models. LSE STICERD Research Paper No. EM/2010/551.
    • Koo, B., Linton, O., 2010. Semiparametric estimation of locally stationary diffusion models. LSE STICERD Research Paper No. EM/2010/551.
    • (2010)
    • Koo, B.1    Linton, O.2
  • 67
    • 84861389362 scopus 로고    scopus 로고
    • Bootstrapping Locally Stationary Processes. Technical report.
    • Kreiss, J.-P., Paparoditis, E., 2011. Bootstrapping Locally Stationary Processes. Technical report.
    • (2011)
    • Kreiss, J.-P.1    Paparoditis, E.2
  • 69
    • 0017526570 scopus 로고
    • Analysis of recursive stochastic algorithms
    • Ljung L. Analysis of recursive stochastic algorithms. IEEE Trans. Automat. Contr. 1977, 22:551-575.
    • (1977) IEEE Trans. Automat. Contr. , vol.22 , pp. 551-575
    • Ljung, L.1
  • 73
    • 24344506203 scopus 로고    scopus 로고
    • Statistical inference for time-inhomogenous volatility models
    • Mercurio D., Spokoiny V. Statistical inference for time-inhomogenous volatility models. Ann. Stat. 2004, 32:577-602.
    • (2004) Ann. Stat. , vol.32 , pp. 577-602
    • Mercurio, D.1    Spokoiny, V.2
  • 74
    • 21844492815 scopus 로고
    • Parameter estimation for ARMA models with infinite variance innovations
    • Mikosch T., Gadrich T., Klüppelberg C., Adler R.J. Parameter estimation for ARMA models with infinite variance innovations. Ann. Stat. 1995, 23:305-326.
    • (1995) Ann. Stat. , vol.23 , pp. 305-326
    • Mikosch, T.1    Gadrich, T.2    Klüppelberg, C.3    Adler, R.J.4
  • 75
    • 0031256319 scopus 로고    scopus 로고
    • Uniform convergence of the empirical spectral distribution function
    • Mikosch T., Norvaisa R. Uniform convergence of the empirical spectral distribution function. Stoch. Proc. Appl. 1997, 70:85-114.
    • (1997) Stoch. Proc. Appl. , vol.70 , pp. 85-114
    • Mikosch, T.1    Norvaisa, R.2
  • 76
    • 12144287086 scopus 로고    scopus 로고
    • Nonstationarities in financial time series, the long-range dependence, and the IGARCH effects
    • Mikosch T., Stǎricǎ C. Nonstationarities in financial time series, the long-range dependence, and the IGARCH effects. Rev. Econ. Stat. 2004, 86:378-390.
    • (2004) Rev. Econ. Stat. , vol.86 , pp. 378-390
    • Mikosch, T.1    Stǎricǎ, C.2
  • 77
    • 79956346969 scopus 로고    scopus 로고
    • Locally stationary factor models: Identification and nonparametric estimation
    • page 1-41, doi:10.1017/S026646661100005
    • Motta G., Hafner C.M., von Sachs R. Locally stationary factor models: Identification and nonparametric estimation. Econom. Theory 2011, 27(6):1279-1319. page 1-41. doi:10.1017/S026646661100005.
    • (2011) Econom. Theory , vol.27 , Issue.6 , pp. 1279-1319
    • Motta, G.1    Hafner, C.M.2    von Sachs, R.3
  • 78
    • 33644917699 scopus 로고    scopus 로고
    • On recursive estimation for locally stationary time varying autoregressive processes
    • Moulines E., Priouret P., Roueff F. On recursive estimation for locally stationary time varying autoregressive processes. Ann. Stat. 2005, 33:2610-2654.
    • (2005) Ann. Stat. , vol.33 , pp. 2610-2654
    • Moulines, E.1    Priouret, P.2    Roueff, F.3
  • 80
    • 0034354958 scopus 로고    scopus 로고
    • Wavelet processes and adaptive estimation of evolutionary wavelet spectra
    • Nason G.P., von Sachs R., Kroisandt G. Wavelet processes and adaptive estimation of evolutionary wavelet spectra. J. R. Stat. Soc. B 2000, 62:271-292.
    • (2000) J. R. Stat. Soc. B , vol.62 , pp. 271-292
    • Nason, G.P.1    von Sachs, R.2    Kroisandt, G.3
  • 81
    • 0031517528 scopus 로고    scopus 로고
    • Wavelet thresholding in anisotropic function classes and applications to adaptive estimation of evolutionary spectra
    • Neumann M.H., von Sachs R. Wavelet thresholding in anisotropic function classes and applications to adaptive estimation of evolutionary spectra. Ann. Stat. 1997, 25:38-76.
    • (1997) Ann. Stat. , vol.25 , pp. 38-76
    • Neumann, M.H.1    von Sachs, R.2
  • 82
    • 85012564551 scopus 로고    scopus 로고
    • Automatic statistical analysis of bivariate nonstationary time series
    • Ombao H.C., Raz J.A., von Sachs R., Malow B.A. Automatic statistical analysis of bivariate nonstationary time series. J. Am. Stat. Assoc. 2001, 96:543-560.
    • (2001) J. Am. Stat. Assoc. , vol.96 , pp. 543-560
    • Ombao, H.C.1    Raz, J.A.2    von Sachs, R.3    Malow, B.A.4
  • 83
  • 84
    • 20444432356 scopus 로고    scopus 로고
    • The SLEX analysis of multivariate non-stationary time series
    • Ombao H.C., von Sachs R., Guo W. The SLEX analysis of multivariate non-stationary time series. J. Am. Stat. Assoc. 2005, 100:519-531.
    • (2005) J. Am. Stat. Assoc. , vol.100 , pp. 519-531
    • Ombao, H.C.1    von Sachs, R.2    Guo, W.3
  • 85
    • 0001594865 scopus 로고    scopus 로고
    • A nonparametric method to estimate time varying coefficients
    • Orbe S., Ferreira E., Rodriguez-Poo R.M. A nonparametric method to estimate time varying coefficients. J. Nonparam. Stat. 2000, 12:779-806.
    • (2000) J. Nonparam. Stat. , vol.12 , pp. 779-806
    • Orbe, S.1    Ferreira, E.2    Rodriguez-Poo, R.M.3
  • 86
    • 10444280095 scopus 로고    scopus 로고
    • Nonparametric estimation of time varying parameters under shape restrictions
    • Orbe S., Ferreira E., Rodriguez-Poo R.M. Nonparametric estimation of time varying parameters under shape restrictions. J. Econom. 2005, 126:53-77.
    • (2005) J. Econom. , vol.126 , pp. 53-77
    • Orbe, S.1    Ferreira, E.2    Rodriguez-Poo, R.M.3
  • 88
    • 77957586838 scopus 로고    scopus 로고
    • An efficient estimator for locally stationary Gaussian long-memory processes
    • Palma W., Olea R. An efficient estimator for locally stationary Gaussian long-memory processes. Ann. Stat. 2010, 38:2958-2997.
    • (2010) Ann. Stat. , vol.38 , pp. 2958-2997
    • Palma, W.1    Olea, R.2
  • 89
    • 77649221152 scopus 로고    scopus 로고
    • Testing temporal constancy of the spectral structure of a time series
    • Paparoditis E. Testing temporal constancy of the spectral structure of a time series. Bernoulli 2009, 15:1190-1221.
    • (2009) Bernoulli , vol.15 , pp. 1190-1221
    • Paparoditis, E.1
  • 90
    • 78649423525 scopus 로고    scopus 로고
    • Validating stationarity assumptions in time series analysis by rolling local periodograms
    • Paparoditis E. Validating stationarity assumptions in time series analysis by rolling local periodograms. J. Amer. Statist. Assoc. 2010, 105:839-851.
    • (2010) J. Amer. Statist. Assoc. , vol.105 , pp. 839-851
    • Paparoditis, E.1
  • 92
    • 0001761543 scopus 로고
    • Autoregressive spectral estimation
    • North-Holland, Amsterdam, 3, D.R. Brillinger, P.R. Krishnaiah (Eds.)
    • Parzen E. Autoregressive spectral estimation. Handbook of Statistics 1983, 221-247. North-Holland, Amsterdam, 3. D.R. Brillinger, P.R. Krishnaiah (Eds.).
    • (1983) Handbook of Statistics , pp. 221-247
    • Parzen, E.1
  • 93
    • 0001529844 scopus 로고
    • Testing and estimating change-points in time series
    • Picard D. Testing and estimating change-points in time series. Adv. Appl. Probab. 1985, 17:841-867.
    • (1985) Adv. Appl. Probab. , vol.17 , pp. 841-867
    • Picard, D.1
  • 94
    • 84861392830 scopus 로고    scopus 로고
    • Testing semiparametric hypotheses in locally stationary processes. Discussion paper 13/11. SFB 823, TU Dortmund.
    • Preuß, P., Vetter, M., Dette, H., 2011. Testing semiparametric hypotheses in locally stationary processes. Discussion paper 13/11. SFB 823, TU Dortmund.
    • (2011)
    • Preuß, P.1    Vetter, M.2    Dette, H.3
  • 95
    • 0001550082 scopus 로고
    • Evolutionary spectra and non-stationary processes
    • Priestley M.B. Evolutionary spectra and non-stationary processes. J. R. Stat. Soc. Ser. B 1965, 27:204-237.
    • (1965) J. R. Stat. Soc. Ser. B , vol.27 , pp. 204-237
    • Priestley, M.B.1
  • 98
    • 0000110918 scopus 로고
    • A test for non-stationarity of time series
    • Priestley M.B., Subba Rao T. A test for non-stationarity of time series. J. R. Stat. Soc. B 1969, 31:140-149.
    • (1969) J. R. Stat. Soc. B , vol.31 , pp. 140-149
    • Priestley, M.B.1    Subba Rao, T.2
  • 100
    • 21344446855 scopus 로고
    • Gaussian semiparametric estimation of long range dependence
    • Robinson P.M. Gaussian semiparametric estimation of long range dependence. Ann. Stat. 1995, 23:1630-1661.
    • (1995) Ann. Stat. , vol.23 , pp. 1630-1661
    • Robinson, P.M.1
  • 101
    • 70350303354 scopus 로고    scopus 로고
    • Local Spectral Analysis via a Bayesian Mixture of Smoothing Splines
    • Rosen O., Stoffer D.S., Wood S. Local Spectral Analysis via a Bayesian Mixture of Smoothing Splines. J. Am. Stat. Assoc. 2009, 104:249-262.
    • (2009) J. Am. Stat. Assoc. , vol.104 , pp. 249-262
    • Rosen, O.1    Stoffer, D.S.2    Wood, S.3
  • 102
    • 79951674301 scopus 로고    scopus 로고
    • Locally stationary long memory estimation
    • Roueff F., von Sachs R. Locally stationary long memory estimation. Stoch. Proc. Appl. 2011, 121:813-844.
    • (2011) Stoch. Proc. Appl. , vol.121 , pp. 813-844
    • Roueff, F.1    von Sachs, R.2
  • 103
    • 77952792812 scopus 로고    scopus 로고
    • Estimating linear dependence between nonstationary time series using the locally stationary wavelet model
    • Sanderson J., Fryzlewicz P., Jones M. Estimating linear dependence between nonstationary time series using the locally stationary wavelet model. Biometrika 2010, 97:435-446.
    • (2010) Biometrika , vol.97 , pp. 435-446
    • Sanderson, J.1    Fryzlewicz, P.2    Jones, M.3
  • 104
    • 0141976688 scopus 로고    scopus 로고
    • Testing composite hypotheses for locally stationary processes
    • Sakiyama K., Taniguchi M. Testing composite hypotheses for locally stationary processes. J. Time Ser. Anal. 2003, 24:483-504.
    • (2003) J. Time Ser. Anal. , vol.24 , pp. 483-504
    • Sakiyama, K.1    Taniguchi, M.2
  • 105
    • 3042640076 scopus 로고    scopus 로고
    • Discriminant analysis for locally stationary processes
    • Sakiyama K., Taniguchi M. Discriminant analysis for locally stationary processes. J. Multiv. Anal. 2004, 90:282-300.
    • (2004) J. Multiv. Anal. , vol.90 , pp. 282-300
    • Sakiyama, K.1    Taniguchi, M.2
  • 106
    • 84985657441 scopus 로고
    • Adaptive methods of trend detection and their application in analyzing biosignals
    • Schack B., Grieszbach G. Adaptive methods of trend detection and their application in analyzing biosignals. Biom. J. 1994, 36:429-452.
    • (1994) Biom. J. , vol.36 , pp. 429-452
    • Schack, B.1    Grieszbach, G.2
  • 107
    • 39749185919 scopus 로고    scopus 로고
    • Bootstrapping the Local Periodogram of Locally Stationary Processes
    • Corrigendum: J. Time Ser. Anal. 30, 260-261
    • Sergides M., Paparoditis E. Bootstrapping the Local Periodogram of Locally Stationary Processes. J. Time Ser. Anal. 2008, 29:264-299. Corrigendum: J. Time Ser. Anal. 30, 260-261.
    • (2008) J. Time Ser. Anal. , vol.29 , pp. 264-299
    • Sergides, M.1    Paparoditis, E.2
  • 108
    • 70350492994 scopus 로고    scopus 로고
    • Frequency domain tests of semiparametric hypotheses for locally stationary processes
    • Sergides M., Paparoditis E. Frequency domain tests of semiparametric hypotheses for locally stationary processes. Scandin. J. Stat. 2009, 36:800-821.
    • (2009) Scandin. J. Stat. , vol.36 , pp. 800-821
    • Sergides, M.1    Paparoditis, E.2
  • 109
    • 33846438586 scopus 로고    scopus 로고
    • Statistical estimation of optimal portfolios for locally stationary returns of assets
    • Shiraishi H., Taniguchi M. Statistical estimation of optimal portfolios for locally stationary returns of assets. Int. J. Theor. Appl. Finance 2007, 10:129-154.
    • (2007) Int. J. Theor. Appl. Finance , vol.10 , pp. 129-154
    • Shiraishi, H.1    Taniguchi, M.2
  • 111
    • 23844552784 scopus 로고    scopus 로고
    • Nonstationarities in stock returns
    • Stǎricǎ C., Granger C. Nonstationarities in stock returns. Rev. Econ. Stat. 2005, 87:503-522.
    • (2005) Rev. Econ. Stat. , vol.87 , pp. 503-522
    • Stǎricǎ, C.1    Granger, C.2
  • 112
    • 33846963859 scopus 로고    scopus 로고
    • On some nonstationary, nonlinear random processes and their stationary approximations
    • Subba Rao S. On some nonstationary, nonlinear random processes and their stationary approximations. Adv. Appl. Probab. 2006, 38:1155-1172.
    • (2006) Adv. Appl. Probab. , vol.38 , pp. 1155-1172
    • Subba Rao, S.1
  • 113
    • 0000777281 scopus 로고
    • The fitting of non-stationary time series models with time-dependent parameters
    • Subba Rao T. The fitting of non-stationary time series models with time-dependent parameters. J. R. Stat. Soc. B 1970, 32:312-322.
    • (1970) J. R. Stat. Soc. B , vol.32 , pp. 312-322
    • Subba Rao, T.1
  • 114
    • 58149141903 scopus 로고    scopus 로고
    • Second order properties of locally stationary processes
    • Tamaki K. Second order properties of locally stationary processes. J. Time Ser. Anal. 2009, 30:145-166.
    • (2009) J. Time Ser. Anal. , vol.30 , pp. 145-166
    • Tamaki, K.1
  • 117
    • 0011460758 scopus 로고
    • Spectral generating operators for non-stationary processes
    • Tjøstheim D. Spectral generating operators for non-stationary processes. Adv. Appl. Probab. 1976, 8:831-846.
    • (1976) Adv. Appl. Probab. , vol.8 , pp. 831-846
    • Tjøstheim, D.1
  • 118
    • 84861406666 scopus 로고    scopus 로고
    • On the optimal segment length for tapered Yule-Walker estimates for time-varying autoregressive processes. Diploma Thesis, Heidelberg.
    • Tunyavetchakit, S., 2010. On the optimal segment length for tapered Yule-Walker estimates for time-varying autoregressive processes. Diploma Thesis, Heidelberg.
    • (2010)
    • Tunyavetchakit, S.1
  • 119
    • 33750351995 scopus 로고    scopus 로고
    • Semiparametric estimation by model selection for locally stationary processes
    • Van Bellegem S., Dahlhaus R. Semiparametric estimation by model selection for locally stationary processes. J. R. Stat. Soc. B 2006, 68:721-764.
    • (2006) J. R. Stat. Soc. B , vol.68 , pp. 721-764
    • Van Bellegem, S.1    Dahlhaus, R.2
  • 120
    • 13844315150 scopus 로고    scopus 로고
    • Forecasting economic time series with unconditional time varying variance
    • Van Bellegem S., von Sachs R. Forecasting economic time series with unconditional time varying variance. Int. J. Forecast. 2004, 20:611-627.
    • (2004) Int. J. Forecast. , vol.20 , pp. 611-627
    • Van Bellegem, S.1    von Sachs, R.2
  • 121
    • 51049117978 scopus 로고    scopus 로고
    • Locally adaptive estimation of evolutionary wavelet spectra
    • Van Bellegem S., von Sachs R. Locally adaptive estimation of evolutionary wavelet spectra. Ann. Stat. 2008, 36:1879-1924.
    • (2008) Ann. Stat. , vol.36 , pp. 1879-1924
    • Van Bellegem, S.1    von Sachs, R.2
  • 123
    • 84861389360 scopus 로고    scopus 로고
    • Nonparametric regression for locally stationary time series. Preprint, University of Mannheim.
    • Vogt, M., 2011. Nonparametric regression for locally stationary time series. Preprint, University of Mannheim.
    • (2011)
    • Vogt, M.1
  • 124
    • 0001479617 scopus 로고    scopus 로고
    • A wavelet-based test for stationarity
    • von Sachs R., Neumann M. A wavelet-based test for stationarity. J. Time Ser. Anal. 2000, 21:597-613.
    • (2000) J. Time Ser. Anal. , vol.21 , pp. 597-613
    • von Sachs, R.1    Neumann, M.2
  • 126
    • 0000751392 scopus 로고
    • Estimation and information in stationary time series
    • Whittle P. Estimation and information in stationary time series. Ark. Mat. 1953, 2:423-434.
    • (1953) Ark. Mat. , vol.2 , pp. 423-434
    • Whittle, P.1
  • 127
    • 84861389361 scopus 로고
    • Some recent contributions to the theory of stationary processes. Appendix to A study in the analysis of stationary time series, by H. Wold, 2nd ed. 196-228. Almqvist and Wiksell, Uppsala.
    • Whittle, P., 1954. Some recent contributions to the theory of stationary processes. Appendix to A study in the analysis of stationary time series, by H. Wold, 2nd ed. 196-228. Almqvist and Wiksell, Uppsala.
    • (1954)
    • Whittle, P.1
  • 128
    • 79958280852 scopus 로고    scopus 로고
    • Gaussian approximations for non-stationary multiple time series
    • Wu W.B., Zhou Z. Gaussian approximations for non-stationary multiple time series. Statistica Sinica 2011, 21:1397-1413.
    • (2011) Statistica Sinica , vol.21 , pp. 1397-1413
    • Wu, W.B.1    Zhou, Z.2
  • 129
    • 0036271917 scopus 로고    scopus 로고
    • Large deviations for quadratic forms of locally stationary processes
    • Zani M. Large deviations for quadratic forms of locally stationary processes. J. Multivar. Anal. 2002, 81:205-228.
    • (2002) J. Multivar. Anal. , vol.81 , pp. 205-228
    • Zani, M.1
  • 130
    • 77955126247 scopus 로고    scopus 로고
    • Nonparametric inference of quantile curves for nonstationary time series
    • Zhou Z. Nonparametric inference of quantile curves for nonstationary time series. Ann. Stat. 2010, 38:2187-2217.
    • (2010) Ann. Stat. , vol.38 , pp. 2187-2217
    • Zhou, Z.1
  • 131
    • 69149110260 scopus 로고    scopus 로고
    • Local linear quantile estimation for non-stationary time series
    • Zhou Z., Wu W.B. Local linear quantile estimation for non-stationary time series. Ann. Stat. 2009, 37:2696-2729.
    • (2009) Ann. Stat. , vol.37 , pp. 2696-2729
    • Zhou, Z.1    Wu, W.B.2
  • 132
    • 78650349691 scopus 로고    scopus 로고
    • Simultaneous inference of linear models with time varying coefficients
    • Zhou Z., Wu W.B. Simultaneous inference of linear models with time varying coefficients. J. R. Stat. Soc. B 2010, 72:513-531.
    • (2010) J. R. Stat. Soc. B , vol.72 , pp. 513-531
    • Zhou, Z.1    Wu, W.B.2


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