Statistical analysis of time series with scaling indices.
Statistical tools for discovering pseudo-periodicities in biological sequences
Many protein sequences present non trivial periodicities, such as cysteine signatures and leucine heptads. These known periodicities probably represent a small percentage of the total number of sequences periodic structures, and it is useful to have general tools to detect such sequences and their period in large databases of sequences. We compare three statistics adapted from those used in time series analysis: a generalisation of the simple autocovariance based on a similarity score and two statistics...
Statistical tools for discovering pseudo-periodicities in biological sequences
Many protein sequences present non trivial periodicities, such as cysteine signatures and leucine heptads. These known periodicities probably represent a small percentage of the total number of sequences periodic structures, and it is useful to have general tools to detect such sequences and their period in large databases of sequences. We compare three statistics adapted from those used in time series analysis: a generalisation of the simple autocovariance based on a similarity score and two statistics...
Statistique asymptotique presque-sûre de modèles statistiques convexes
Study of a least-squares-based algorithm for autoregressive signals subject to white noise.
Study on Kalman filter in time series analysis
Subspace-based methods to determine unit roots and cointegrating ranks.
Superposition of diffusions with linear generator and its multifractal limit process
In this paper a new multifractal stochastic process called Limit of the Integrated Superposition of Diffusion processes with Linear differencial Generator (LISDLG) is presented which realistically characterizes the network traffic multifractality. Several properties of the LISDLG model are presented including long range dependence, cumulants, logarithm of the characteristic function, dilative stability, spectrum and bispectrum. The model captures higher-order statistics by the cumulants. The relevance...
Superposition of Diffusions with Linear Generator and its Multifractal Limit Process
In this paper a new multifractal stochastic process called Limit of the Integrated Superposition of Diffusion processes with Linear differencial Generator (LISDLG) is presented which realistically characterizes the network traffic multifractality. Several properties of the LISDLG model are presented including long range dependence, cumulants, logarithm of the characteristic function, dilative stability, spectrum and bispectrum. The model captures higher-order statistics by the cumulants. The relevance...
Sur la loi des grands nombres pour les martingales vectorielles et l'estimateur des moindres carrés d'un modèle de régression
Sur l'estimateur des moindres carrés généralisé d'un modèle ARMAX. Application à l'identification des modèles ARMA
Tables for processes with exponential white noise
Test de hipótesis para contrastar modelos MARMA de series temporales.
El propósito de este artículo es revisar, relacionar e interpretar tests de hipótesis, tipo score, para contrastar la especificación de modelos de series temporales múltiples, así como obtener unos resultados sobre los estadísticos asociados, lo más simples posibles, a fin de utilizarlos en la etapa de identificación de los modelos.
Testing a sub-hypothesis in linear regression models with long memory covariates and errors
This paper considers the problem of testing a sub-hypothesis in homoscedastic linear regression models when the covariate and error processes form independent long memory moving averages. The asymptotic null distribution of the likelihood ratio type test based on Whittle quadratic forms is shown to be a chi-square distribution. Additionally, the estimators of the slope parameters obtained by minimizing the Whittle dispersion is seen to be -consistent for all values of the long memory parameters...
Testing linearity and modelling nonlinear time series
Testing Linearity in an AR Errors-in-variables Model with Application to Stochastic Volatility
Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given data set, a statistical test is required. In this paper, we develop such a test of a linear hypothesis versus a general composite nonparametric alternative using the state space representation of the SV model as an errors-in-variables AR(1) model. The power of the test is analyzed. We provide a simulation study and apply the test to the HFDF96...
Testing on the first-order autoregressive model with contaminated exponential white noise finite sample case
The testing problem on the first-order autoregressive parameter in finite sample case is considered. The innovations are distributed according to the exponential distribution. The aim of this paper is to study how much the size of this test changes when, at some time k, an innovation outlier contaminant occurs. We show that the test is rather sensitive to these changes.
Tests for the presence of trends in linear processes [Book]
Tests simultanés de permutation des rangs pour bruit-blanc multivarié
The Behaviour of the Lagrangian Multiplier Test in Testing the Orders of an ARMA-Model.