Tail-behaviour of location estimators in non-regular cases
Teorie ověřování statistických hypothes [Dokončení]
Test for exponentiality against Weibull and gamma decreasing hazard rate alternatives
A sub-exponential Weibull random variable may be expressed as a quotient of a unit exponential to an independent strictly positive stable random variable. Based on this property, we propose a test for exponentiality which is consistent against Weibull and Gamma distributions with shape parameter less than unity. A comparison with other procedures is also included.
Test of Hypotheses in some Families of Discrete Distributions
Testing a homogeneity of stochastic processes
The paper concentrates on modeling the data that can be described by a homogeneous or non-homogeneous Poisson process. The goal is to decide whether the intensity of the process is constant or not. In technical practice, e.g., it means to decide whether the reliability of the system remains the same or if it is improving or deteriorating. We assume two situations. First, when only the counts of events are known and, second, when the times between the events are available. Several statistical tests...
Testing a precise null hypothesis using reference posterior odds.
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 a tolerance hypothesis by means of an information distance
In the paper a test of the hypothesis , on parameters of the normal distribution is presented, and explicit formulas for critical regions are derived for finite sample sizes. Asymptotic null distribution of the test statistic is investigated under the assumption, that the true distribution possesses the fourth moment.
Testing Conditional Symmetry Against One-Sided Alternatives in Square Contingency Tables.
Testing for normality
Testing Homogeneity of Ordered Variances.
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 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 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...
Tests de la razón de verosimilitud para medias de poblaciones normales, sujetas a restricciones.
This paper shows the statistics that define the likelihood ratio tests about the mean of a k-dimensional normal population, when the hypotheses to test are H0: θ = 0; H0*: θ ∈ τφ; H1: θ ∈ τ; H2: θ ∈ Rk, being τ a closed and poliedric convex cone in Rk, and τφ the minima dimension face in τ.It is proved that the obtained statistics distributions are certain combinations of chi-squared distributions, when θ = 0.At last, it is proved that the power functions of the tests satisfy some desirable properties....
Tests for relation type - equivalence or tolerance - in a finite set of elements