Pages that link to "Item:Q1766074"

The following pages link to Weak convergence for the covariance operators of a Hilbertian linear process. (Q1766074):

Displaying 31 items.

• Convolutional autoregressive models for functional time series (Q308370) (← links)
• Consistency of the plug-in functional predictor of the Ornstein-Uhlenbeck process in Hilbert and Banach spaces (Q310616) (← links)
• Test of independence for functional data (Q391591) (← links)
• Periodically correlated autoregressive Hilbertian processes (Q453784) (← links)
• An introduction to functional data analysis and a principal component approach for testing the equality of mean curves (Q496981) (← links)
• Conjugate processes: theory and application to risk forecasting (Q681983) (← links)
• Sparse functional principal component analysis in a new regression framework (Q830527) (← links)
• Testing for the mean of random curves: a penalization approach (Q882913) (← links)
• On the asymptotic normality of kernel estimators of the long run covariance of functional time series (Q901286) (← links)
• Hilbert space representations of general discrete time stochastic processes (Q1060483) (← links)
• Large and moderate deviations for infinite-dimensional autoregressive processes. (Q1426344) (← links)
• A survey of functional principal component analysis (Q1621666) (← links)
• Dependent functional data (Q1952694) (← links)
• A weak law of large numbers for realised covariation in a Hilbert space setting (Q2074990) (← links)
• Robust functional principal component analysis based on a new regression framework (Q2102971) (← links)
• SPHARMA approximations for stationary functional time series on the sphere (Q2243556) (← links)
• A note on the cross-covariance operator and on congruence relations for Hilbert space valued stochastic processes (Q2267614) (← links)
• A modification of Silverman's method for smoothed functional principal components analysis (Q2320911) (← links)
• Cramér-Karhunen-Loève representation and harmonic principal component analysis of functional time series (Q2447653) (← links)
• A sufficient condition for the CLT in the space of nuclear operators -- application to covariance of random functions (Q2497812) (← links)
• Assessing extrema of empirical principal component functions (Q2500461) (← links)
• Rates of convergence of autocorrelation estimates for periodically correlated autoregressive Hilbertian processes (Q4632273) (← links)
• Doubly stochastic Hilbertian processes (Q4805839) (← links)
• On an autoregressive process driven by a sequence of Gaussian cylindrical random variables (Q4957785) (← links)
• Functional data clustering using principal curve methods (Q5104527) (← links)
• Testing equality of autocovariance operators for functional time series (Q5121012) (← links)
• On Properties of Functional Principal Components Analysis (Q5434734) (← links)
• INFERENCE ON THE DIMENSION OF THE NONSTATIONARY SUBSPACE IN FUNCTIONAL TIME SERIES (Q6156583) (← links)
• Structural break analysis for spectrum and trace of covariance operators (Q6626124) (← links)
• Functional principal component based landmark analysis for the effects of longitudinal cholesterol profiles on the risk of coronary heart disease (Q6627917) (← links)
• Functional principal component analysis for longitudinal data with informative dropout (Q6627921) (← links)