The classical theory of statistical signal extraction presupposes lengthy data sequences, which are assumed, in theory, to be doubly infinite or semi-infinite— see Whittle (1983), for example. In many practical cases, and in most econometric applications, the available data are, to the contrary, both strongly trended and of a limited duration. This paper is concerned with the theory of finite-s...

In this paper we propose an improvement of the Kolmogorov-Smirnov test for normality. In the current implementation of the Kolmogorov-Smirnov test, a sample is compared with a normal distribution where the sample mean and the sample variance are used as parameters of the distribution. We propose to select the mean and variance of the normal distribution that provide the closest fit to the data....

The Kolmogorov-Smirnov (K-S) test is widely used as a goodness-of-fit test. This thesis consists of two parts to describe ways to improve the classical K-S test in both 1-dimensional and 2-dimensional data. The first part is about how to improve the accuracy of the classical K-S goodness-of-fit test in 1-dimensional data. We replace the p-values estimated by the asymptotic distribution with nea...

In this paper the Kolmogorov-Smirnov statistical test for the analysis of histograms is presented. The test is discussed for both the two-sample case (comparing fn1(X) to fn2 (X)) and the one-sample case (comparing fn1 (X) to f(X)). Presentation of the specific algorithmic steps involved is done through development of an example where the data are from an experiment discussed elsewhere in this ...