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Fitting the Negative Binomial Distribution
Biometrics, 1986This note is a reaction to recent papers in this journal by Willson, Folks, and Young (1984) and Bowman (1984). For the biometrical analysis of certain kinds of observations, such as insect counts, accident counts, or cave entrance counts, when only nonnegative integers are observable, it is expedient to restrict attention to those random variables ...
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Empirical Fitting of Discrete Distributions
Biometrics, 1994SUMMARY Short-tailed observed frequency distributions are often well fitted by a number of different theoretical discrete distributions, with little discriminatory power. An example is used to suggest how this may be carried further in some situations.
J. B. Douglas +2 more
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1995
Abstract Categorical data models have traditionally been used to study nominal, and ordinal, response variables. However, empirically, ‘continuous’ variables are also always observed as discrete categories, defined by the precision of the measuring instrument. Thus, log linear modelling techniques can be applied to such data, at least if
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Abstract Categorical data models have traditionally been used to study nominal, and ordinal, response variables. However, empirically, ‘continuous’ variables are also always observed as discrete categories, defined by the precision of the measuring instrument. Thus, log linear modelling techniques can be applied to such data, at least if
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Fitness Distributions and GA Hardness
2004Considerable research effort has been spent in trying to formulate a good definition of GA-Hardness. Given an instance of a problem, the objective is to estimate the performance of a GA. Despite partial successes current definitions are still unsatisfactory.
Yossi Borenstein, Riccardo Poli
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Fitting Distributions to Random Parameters
Transportation Research Record: Journal of the Transportation Research Board, 2006This research investigated the choice of distributions for the parameters of a mixed logit model, under the risk that the model appears statistically successful when its actual fit to the true behavior is poor. A subsampling technique is used to examine the aptitude of several model specifications to approximate the range of preferences of bus ...
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GOODNESS OF FIT FOR THE BINOMIAL DISTRIBUTION
Australian Journal of Statistics, 1997SummaryGoodness of fit testing for the binomial distribution can be carried out using Pearson's X2p statistic and its components. Applications of this technique are considered and compared with recently suggested empirical distribution function tests. Diagnostic use of components is discussed.
Best, D. J., Rayner, J. C. W.
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Cumulative Frequency Fit for Particle Size Distribution
Applied Occupational and Environmental Hygiene, 2002A cumulative frequency distribution fit method is presented for analyzing particle size distributions by minimizing the summation of the square of cumulative frequency errors. Compared to the frequency fit method, the cumulative frequency fit method yields a more accurate solution.
Zhuyun, Xu +2 more
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Fitting with Matrix-Exponential Distributions
Stochastic Models, 2005Abstract It is well known that general phase-type distributions are considerably overparameterized, that is, their representations often require many more parameters than is necessary to define the distributions. In addition, phase-type distributions, even those defined by a small number of parameters, may have representations of high order.
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Fitting the Truncated Pareto Distribution to Loss Distributions
Journal of the Staple Inn Actuarial Society, 1988Hogg and Klugman use the truncated Pareto distribution with probability density functionwhere δ≥0 is specified and α > 0 and λ > 0 are unknown parameters, to describe insurance claims. This is fitted first of all by the method of moments, using the estimatorsand where is the mean of a simple random sample, and the (biased) varianceThe authors ...
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Examples of fitting structured phase–type distributions
Applied Stochastic Models and Data Analysis, 1994AbstractA sub–class of phase–type distributions is defined in terms of a Markov process with sequential transitions between transient states and transitions from these states to absorption. Such distributions form a very rich class; they can be fitted to data, and any structure revealed by the parameter estimates used to develop more parsimonious re ...
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