This paper introduces specification tests for conditional moment restrictions. The proposed tests are generalizations of the Kolmogorov–Smirnov and Cramer–von Mises tests and they are consistent against all ] Œ alternatives to the null hypothesis, powerful against 1 / n local alternatives and not dependent on any smoothing parameter. A nonparametric bootstrap procedure based on recentered crite...

This study is based on formulation of a new probability model having four parameters. Parameters the are estimated using Maximum likelihood, Least Square and Cramer –von Mises method. Some statistical properties like reliability function, hazard rate functi on, quantile functions studied. Applicability tested real data set. Box plot TTT plots used to explain nature data. For validation, Q-Q plo...

Nonparametric tests for investigating the separability of a spatial-temporal marked point process are described and compared. It is shown that a Cramer-von Mises-type test is very powerful at detecting gradual departures from separability, and that a residual test based on randomly rescaling the process is powerful at detecting nonseparable clustering or inhibition of the marks. An application ...

This paper make an overview of the copula theory from a practical side. We consider different methods of copula estimation and different Goodness-of-Fit tests for model selection. In the GoF section we apply Kolmogorov-Smirnov and Cramer-von-Mises type tests and calculate power of these tests under different assumptions. Novating in this paper is that all the procedures are done in dimensions h...

In this chapter, we consider some chi-square-type goodness-of-fit tests for right AQ1 censored samples, viz. the Nikulin–Rao–Robson (NRR) test and generalized Pearson–Fisher (GPF) test. We compare these tests in terms of power in the case of testing composite hypotheses by randomly censored and Type II censored samples. Various grouping methods are considered, including equifrequent grouping, g...

This paper considers the problem of estimation and inference in semiparametric varying coefficients models when the response variable is subject to random censoring. The paper proposes an estimator based on combining inverse probability censoring weighting and profile least squares estimation. The resulting estimator is shown to be asymptotically normal. The paper proposes three test statistics...

We consider the goodness of fit testing problem for stochastic differential equation with small diffusion coefficient. The basic hypothesis is always simple and it is described by the known trend coefficient. We propose several tests of the type of Cramer-von Mises, Kolmogorov-Smirnov and Chi-Square. The power functions of these tests we study for a special classes of close alternatives. We dis...

Recent work on nonparametric identification of average partial effects (APEs) from panel data require restrictions on individual or time heterogeneity. Identifying assumptions under the “generalized first-differencing” category, such as time homogeneity (Chernozhukov, Fernandez-Val, Hahn, and Newey, 2013), have testable equality restrictions on the distribution of the outcome variable. This pap...

This paper derives asymptotic approximations to the power of Cramer-von Mises (CvM) style tests for inference on a finite dimensional parameter defined by conditional moment inequalities in the case where the parameter is set identified. Combined with power results for Kolmogorov-Smirnov (KS) tests, these results can be used to choose the optimal test statistic, weighting function and, for test...