Testing block sphericity of a covariance matrix.
Testing Conditional Symmetry Against One-Sided Alternatives in Square Contingency Tables.
Testing for normality
Testing for periodicity in signals: An application to detect partial upper airway obstruction during sleep.
Testing Homogeneity of Ordered Variances.
Testing hypotheses in universal models
A linear regression model, when a design matrix has not full column rank and a covariance matrix is singular, is considered. The problem of testing hypotheses on mean value parameters is studied. Conditions when a hypothesis can be tested or when need not be tested are given. Explicit forms of test statistics based on residual sums of squares are presented.
Testing hypothesis for the shift parameter in diffusion processes
Testing in locally conic models, and application to mixture models
Testing in locally conic models, and application to mixture models
In this paper, we address the problem of testing hypotheses using maximum likelihood statistics in non identifiable models. We derive the asymptotic distribution under very general assumptions. The key idea is a local reparameterization, depending on the underlying distribution, which is called locally conic. This method enlights how the general model induces the structure of the limiting distribution in terms of dimensionality of some derivative space. We present various applications of...
Testing in stationary models based on divergences of observed and theoretical frequencies
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.
Testing on the recurrence of coefficients in the linear regressional model.
Testing One-Sided Hypotheses for the Mean of a Gaussian Process.
Testing randomness of spatial point patterns with the Ripley statistic
Aggregation patterns are often visually detected in sets of location data. These clusters may be the result of interesting dynamics or the effect of pure randomness. We build an asymptotically Gaussian test for the hypothesis of randomness corresponding to a homogeneous Poisson point process. We first compute the exact first and second moment of the Ripley K-statistic under the homogeneous Poisson point process model. Then we prove the asymptotic normality of a vector of such statistics for different...
Testing stationary processes for independence
Let H0 denote the class of all real valued i.i.d. processes and H1 all other ergodic real valued stationary processes. In spite of the fact that these classes are not countably tight we give a strongly consistent sequential test for distinguishing between them.
Testing statistical hypotheses in deformation measurement; one generalization of the Scheffé theorem
Testing the independence of two Poisson processes.
Testing the stability of regression parameters when some additional data sets are available.