Person:
Morales González, Domingo

Profile Picture
First Name
Domingo
Last Name
Morales González
URI
https://hdl.handle.net/20.500.14352/83591
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Ciencias Matemáticas
Department
Area
Estadística e Investigación Operativa
Identifiers
UCM identifierORCIDScopus Author IDWeb of Science ResearcherIDDialnet IDGoogle Scholar ID

Filters

20053
Reset filters

Settings

Start date: 1990 × Subject: 519.22 ×

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Choosing the best Rukhin goodness-of-fit statistics
    (Computational Statistics and Data Analysis, 2005) Marhuenda García, Yolanda; Morales González, Domingo; Pardo Llorente, Julio Ángel; Pardo Llorente, María del Carmen
    The testing for goodness-of-fit in multinomial sampling contexts is usually based on the asymptotic distribution of Pearson-type chi-squared statistics. However, approximations are not justified for those cases where sample size and number of cells permit the use of adequate algorithms to calculate the exact distribution of test statistics in a reasonable time. In particular, Rukhin statistics, containing chi(2) and Neyman's modified chi(2) statistics, are considered for testing uniformity. Their exact distributions are calculated for different sample sizes and number of cells. Several exact power comparisons are carried out to analyse the behaviour of selected statistics. As a result of the numerical study some recommendations are given. Conclusions may be extended to testing the goodness of fit to a given absolutely continuous cumulative distribution function.
  • No Thumbnail Available
    Item
    Rukhin's uniformity test based on sample quantiles
    (Journal of Statistical Computation and Simulation, 2005) Marhuenda García, Yolanda; Morales González, Domingo; Pardo Llorente, Julio Ángel; Pardo Llorente, María del Carmen
    The problem of testing if a given probability distribution fits to a set of independent and identically distributed observations is usually treated by categorizing the data range. Discretization can be done by means of relative frequencies or by using sample quantiles. In this article, quantile-based test statistics are proposed to test the hypothesis of uniformity in the interval (0, 1). Exact critical values of the family of Rukhin's statistics are estimated. A Monte Carlo simulation experiment is carried out to calculate powers of these tests in different alternatives. Results obtained from each kind of categorization are compared to give several recommendations about the use of Rukhin's statistics and type of categorization.
  • Thumbnail Image
    Item
    A comparison of uniformity tests
    (Statistics: A Journal of Theoretical and Applied Statistics, 2005) Marhuenda García, Yolanda; Morales González, Domingo; Pardo Llorente, María del Carmen
    Problems of goodness-of-fit to a given distribution can usually be reduced to test uniformity. The uniform distribution appears due to natural random events or due to the application of methods for transforming samples from any other distribution to the samples with values uniformily distributed in the interval (0,1), Thus, one can solve the problem of testing if a sample comes from a given distribution by testing whether its transformed sample is distributed according to the uniform distribution. For this reason, the methods of testing for goodness-of-fit to a uniform distribution have been widely investigated. In this paper, a comparative power analysis of a selected set of statistics is performed in order to give suggestions on which one to use for testing uniformity against the families of alternatives proposed by Stephens [Stephens, M.A., 1974, EDF statistics for goodness of fit and some comparisons. Journal of the American Statistical Association, 69, 730-737.]. Definition and some relevant features of the considered test statistics are given in section 1. Implemented numerical processes to calculate percentage points of every considered statistic are described in section 2. Finally, a Monte Carlo simulation experiment has been carried out to fulfill the mentioned target of this paper.