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Estimation in a class of nonlinear heteroscedastic time series models
Conditional least-squares estimation Conditional likelihood estimation Heteroscedastic models Kernel density estimation LATEX2ε
2009/9/16
Parameter estimation in a class of heteroscedastic time series models is investigated. The existence of conditional least-squares and conditional likelihood estimators is proved. Their consistency and...
Modeling threshold exceedance probabilities of spatially correlated time series
threshold exceedance probability PM10 smoothing spatial interpolation spatial time series visualization
2009/9/16
The Commission of the European Union, as well the United States Environmental Protection Agency, have set limit values for some pollutants in the ambient air that have been shown to have adverse effec...
The notion of ψ-weak dependence and its applications to bootstrapping time series
Autoregressive processes autoregressive bootstrap mixing weak dependence.
2009/5/18
We give an introduction to a notion of weak dependence which is more general than mixing and allows to treat for example processes driven by discrete innovations as they appear with time series bootst...
Trend Extraction from Time Series with Structural Breaks and Missing Observations
Break point break point location dummies gaps Hodrick-Prescott filter interpolation Leser filter missing observations smoothing spline structural breaks time-series trend
2009/3/5
Trend extraction from time series is often performed by using the filter proposed by Leser (1961), also known as the Hodrick-Prescott filter. Practical problems arise, however, if the time series cont...
CHANGES OF STRUCTURE IN FINANCIAL TIME SERIES AND THE GARCH MODEL
integrated periodogram spectral distribution functional central limit theorem Kiefer-Muller process Brownian bridge sample autocorrelation change point GARCH process long range dependence IGARCH non-stationarity
2009/2/26
In this paper we propose a goodness of fit test that checks the resemblance of the spectral density of a GARCH process to that of the log-returns. The asymptotic behavior of the test statistics are gi...
A NEW DEPENDENCE CONDITION FOR TIME SERIES AND THE EXTREMAL INDEX OF HIGHER-ORDER MARKOV CHAINS
extremal coefficient dependence extremes extremal index higher-order stationary Markov sequences
2009/2/25
We present a new dependence condition for time series and extend the extremal types
theorem.The dependence structure of a stationary sequence is described by a sequence of
extremal functions. Under ...
ON THE EXTREMES OF RANDOMLY SUB-SAMPLED TIME SERIES
extreme value theory integer-valued stationary sequences sub-sampling failure extremal index
2009/2/25
In this paper, we investigate the extremal properties of randomly sub-sampled stationary
sequences. Motivation comes from the need to account for the effect of missing
values on the analysis of time...
Ultrametric Wavelet Regression of Multivariate Time Series：Application to Colombian Conflict Analysis
Ultrametric Wavelet Regression Multivariate Time Series Colombian Conflict Analysis
2010/3/18
We first pursue the study of how hierarchy provides a well-adapted tool
for the analysis of change. Then, using a time sequence-constrained hi-
erarchical clustering, we develop the practical aspect...
Empirical spectral processes for locally stationary time series
asymptotic normality empirical spectral process locally stationary processes non-stationary time series quadratic forms
2010/3/18
A time-varying empirical spectral process indexed by classes of functions is defined for locally stationary time series. We derive weak convergence in a function space, and prove a maximal exponential...
Modeling threshold exceedance probabilities of spatially correlated time series
threshold exceedance probability PM10 smoothing spatial interpolation spatial time series visualization
2010/3/17
The Commission of the European Union, as well the United
States Environmental Protection Agency, have set limit values for some
pollutants in the ambient air that have been shown to have adverse eff...
Nonparametric spectral analysis with applications to seizure characterization using EEG time series
EEG epilepsy GACV GML locally stationary process permutationtest smoothing parameter smoothing spline SS ANOVA
2010/3/17
Understanding the seizure initiation process and its propagation
pattern(s) is a critical task in epilepsy research. Characteristics of the
pre-seizure electroencephalograms (EEGs) such as oscillati...
Sparse Causal Discovery in Multivariate Time Series
Vector Autoregressive Model Granger Causality Group Lasso Multiple Testing
2010/3/17
Our goal is to estimate causal interactions in multivariate time series.
Using vector autoregressive (VAR) models, these can be defined based on
non-vanishing coecients belonging to respective time...
A mathematical proof of the existence of trends in financial time series
Financial time series mathematical finance technical analysis trends random walks efficient markets
2010/3/17
We are settling a longstanding quarrel in quantitative finance by proving the
existence of trends in financial time series thanks to a theorem due to P. Cartier
and Y. Perrin, which is expressed in ...
Confidence bands in nonparametric time series regression
Long-range dependence model validation moderate deviation nonlinear time series nonparametric regression short-range dependence
2010/4/30
We consider nonparametric estimation of mean regression and
conditional variance (or volatility) functions in nonlinear stochastic
regression models. Simultaneous confidence bands are constructed
a...
Regularly varying multivariate time series
clusters of extremes extremal index heavy tails mixing moving average multivariate regular variation point processes
2010/4/30
A multivariate, stationary time series is said to be jointly regularly
varying if all its finite-dimensional distributions are multivariate regularly
varying. This property is shown to be equivalent...