Using Discrete Distributions to Compute Powers for Goodness-of-Fit Test Statistics in a One-Way Multinomial Setting

1992 ◽  
Vol 34 (4) ◽  
pp. 429-435
Author(s):  
H. B. Lawal
Author(s):  
Lingtao Kong

The exponential distribution has been widely used in engineering, social and biological sciences. In this paper, we propose a new goodness-of-fit test for fuzzy exponentiality using α-pessimistic value. The test statistics is established based on Kullback-Leibler information. By using Monte Carlo method, we obtain the empirical critical points of the test statistic at four different significant levels. To evaluate the performance of the proposed test, we compare it with four commonly used tests through some simulations. Experimental studies show that the proposed test has higher power than other tests in most cases. In particular, for the uniform and linear failure rate alternatives, our method has the best performance. A real data example is investigated to show the application of our test.


2016 ◽  
Vol 14 (1) ◽  
pp. e0201
Author(s):  
Maria-Dolores Huete ◽  
Juan A. Marmolejo

<p>The univariate generalized Waring distribution (UGWD) is presented as a new model to describe the goodness of fit, applicable in the context of agriculture. In this paper, it was used to model the number of olive groves recorded in Spain in the 8,091 municipalities recorded in the 2009 Agricultural Census, according to which the production of oil olives accounted for 94% of total output, while that of table olives represented 6% (with an average of 44.84 and 4.06 holdings per Spanish municipality, respectively). UGWD is suitable for fitting this type of discrete data, with strong left-sided asymmetry. This novel use of UGWD can provide the foundation for future research in agriculture, with the advantage over other discrete distributions that enables the analyst to split the variance. After defining the distribution, we analysed various methods for fitting the parameters associated with it, namely estimation by maximum likelihood, estimation by the method of moments and a variant of the latter, estimation by the method of frequencies and moments. For oil olives, the chi-square goodness of fit test gives <em>p</em>-values of 0.9992, 0.9967 and 0.9977, respectively. However, a poor fit was obtained for the table olive distribution. Finally, the variance was split, following Irwin, into three components related to random factors, external factors and internal differences. For the distribution of the number of olive grove holdings, this splitting showed that random and external factors only account about 0.22% and 0.05%. Therefore, internal differences within municipalities play an important role in determining total variability.</p>


Genome ◽  
1989 ◽  
Vol 32 (1) ◽  
pp. 57-63 ◽  
Author(s):  
S. J. Knapp ◽  
L. A. Tagliani

Genetic markers are needed for mating systems and breeding experiments in Cuphea lanceolata Ait.; however, none have been described in this species. Allozyme variation was analyzed among 14 F2 populations assayed for aconitase (ACO), diaphorase (DIA), esterase (EST), fluorescent esterase transaminase (FEST), glutamine oxaloacetate transaminase (GOT), menadione reductase (MNR), phosphoglucomutase (PGM), phosphoglucose isomerase (PGI), and shikimate dehydrogenase (SKDH) enzyme activity. At least 23 loci were resolved in these enzyme systems: 6 monomorphic loci, 5 poorly resolved loci, and 12 clearly resolved polymorphic loci. Observed segregation ratios were generally not significantly different (P > 0.05) from expected segregation ratios; however, segregation distortion was observed at Skdh-1 and Mnr-1 (Dia-1) in some F2 populations. Skdh-1 and Pgm-2 and Est-1, Est-2, Fest-1, and Mnr-1 comprise putative linkage groups. Allozyme variation was observed between and within accessions. The expected average heterozygosity was 16.3%. There were one to eight polymorphic loci among the F2 populations analyzed. There were an average of 2.05 alleles per locus. Several useful codominant markers were identified and a partial allozyme linkage map was constructed. Additional work is needed to revise and complete the map.Key words: Cuphea, isozymes, goodness of fit test statistics, lauric acid, capric acid.


2018 ◽  
Vol 40 ◽  
pp. 25
Author(s):  
Josmar Mazucheli ◽  
Ricardo Puziol Oliveira ◽  
Danielle Peralta ◽  
Isabele P. Emanuelli

In animal production, the models that mimicry the biological reality are of great importance for optimization and sustainability of the productive system. The continuous Burr XII distribution is widely used in survival data analysis, however, the same does not occur with its discrete version, recently proposed in the literature. The purpose of this work is to use the discrete Burr XII distribution, obtained by the discretization method proposed by Nakagawa and Osaki (1975), in the analysis of data related to animal production. The data analyzed describe the time, in days, from birth to first laying of yellow quail (Coturnix coturnix japonica) submitted to two diets. For this purpose the discretized versions of five distributions were used: the discrete Burr XII, the discrete Weibull, the discrete gamma, the discrete inverse-Gaussian and the discrete log-normal. For all distributions, the parameter estimates were obtained by the maximum likelihood method. Despite the similarity between the estimates it is natural to choose the discrete given the nature of the data and assuming the discrete distribution, it could be calculated exactly, for example, the probability of the time to the first posture, which is not possible if a continuous distribution is assumed. Thus, among the discrete distributions, the chi-square goodness-of-fit test showed that the Burr XII distribution was the only one indicated to describe the behavior of the data considered.


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