# Browsing by Subject "Distribution (Probability theory)"

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Item A multinomial change-point theory in the context of diagnosis code searching(Texas Tech University, 1987-08) Shih, WeiShow more Change-point theory can be described as follows. Consider a sequence of independent random variables, X1, X2,.. Xr, Xr+1,., Xn, in which X1,.., Xr-1 are independently, identically distributed as F1 with parameter Ã¸1, and Xr,...,Xn are distributed as F1 with parameter Ã¸2. The variable r is the change-point. The objective is to determine if a change has occurred and possibly estimate the change-point. The scope of change-point theory is very broad, including essentially all problems in which the stationarity of a sequence of random variables is tested against the possible abrupt change in location, scale or shape of the distributions. In this research, Bayesian change-point theory is extended to multinomial random variables. Using this theory, decision rules are developed for a variety of applications. The major application of multinomial change-point theory discussed in this research is in diagnosis codes searching of the database of the International Classification of Diseases. Ninth Revision, Clinical Modification (ICD-9-CM). This database contains approximately 10,000 diagnosis codes. A hierarchical menu-driven search has been developed to find the correct code. To avoid repeated searches for commonly-used diagnoses, a dynamically changing cache set of the current, most frequently used codes is constructed, and multinomial change-point theory is applied to provide dynamic maintenance of the cache set.Show more Item An empirical modification of the Cornish-Fisher expansion for the F distribution.(Texas Tech University, 1974-08) Herring, Thomas A.Show more Not availableShow more Item Approximations to the noncentral Chi-square and noncentral F distributions(Texas Tech University, 1978-12) Weston, Bill RandallShow more Not availableShow more Item Comparisons of Approximate F Test and A Procedure for the Development of An Alternative.(Texas Tech University, 1974-08) Keenum, Barbara JaneShow more Not Available.Show more Item Conjugate priors and characterization of conjugate priors for power series distributions(Texas Tech University, 1980-08) Lin, Chih ChiangShow more Not availableShow more Item Edgeworth expansions of the Fisher's Z distribution in terms of non-normal distributions(Texas Tech University, 1986-08) Ho, Lun-pinShow more Not availableShow more Item Empirical investigation into the point of departure between the Poisson distribution and the positive or negative binomial distributions for varying means and variance-to-mean ratios(Texas Tech University, 1970-05) Spalding, John BarneyShow more Not availableShow more Item Estimation of the distribution functions of the standardized statistics using Monte Carlo approximation to Edgeworth expansions(Texas Tech University, 2002-05) Gao, GuozhiShow more Not availableShow more Item Finite location mixtures(Texas Tech University, 1998-05) Dissanayake, Gnanadarsha SanjayaShow more Not availableShow more Item Modeling and sensitivity analysis(Texas Tech University, 1998-05) Conover, William J.Show more Not availableShow more Item Numerical calculation of the standard bivariate normal distribution function(Texas Tech University, 1976-12) Tjahjadi, Michael Bernard AgusShow more Not availableShow more Item On Cornish-Fisher Expansions with Unknown Cumulants(Texas Tech University, 1974-05) McCune, Ennis DoniceShow more Not Available.Show more Item One-sided test of fit for discrete probability distribution functions(Texas Tech University, 1970-08) Coberly, William ArthurShow more Not availableShow more Item Polynomials that arise in a Polya urn gambling game(Texas Tech University, 2005-05) Hanlon, Bret M.Show more A gambling game based on the Polya urn process is discussed. Working with the expected value of the game produces an interesting sum. The main result of the paper is this sum is a polynomial with degree equal to the initial number of balls in the urn.Show more Item Simulation of population balance equations using quadrature based moment methods(2006) Upadhyay, Rochan Raj; Ezekoye, Ofodike A.Show more Item Study on the relationship of training data size to error rate and the performance comparison for two decision tree algorithms(Texas Tech University, 2004-08) Zheng, JianjunShow more The decision tree model is a well accepted and widely used classification technique in the data mining field because of its advantages with fast construction, accuracy, and understandability. The decision tree model can be induced through algorithms, such as C4.5 and CART. This thesis research studies the relationship of training data size to error rate for the C4.5 and CART algorithms, and also compares the performance of both of them. Several conclusions are drawn from the results of this thesis research; for example, the well accepted 66.7:33.3 splitting ratio in the literature can be increased to 80:20 for large data sets with more than 1000 samples to generate more accurate decision tree models. This thesis research also shows that the performance of C4.5 and CART on small data sets are similar, but differ on large data sets; therefore, large data sets are more suitable for comparing different algorithms.Show more Item Techniques for Simulating a Bivariate Uniform(Texas Tech University, 1984-05) Chan, Ka-lingShow more Not Available.Show more Item Tests for mixtures of bivariate distributions(Texas Tech University, 1976-05) Shue, Paul TuckerShow more Not availableShow more Item Uncertainties in pressure coefficients derived from full and model scale data / $c by Fei Long.(Texas Tech University, 2004-08) Long, FeiShow more The purpose of this study is to build the uncertainties associated with the wind tunnel testing and full-scale to wind tunnel pressure coefficient extrapolation by comparing the model and full-scale pressure coefficients. Two types of comparisons were made: one is the comparison between the two models CSU & SLM, and the other is the comparison between the models and full-scale (WERFL). For each case, both the observed statistics (i.e., mean, standard deviation, maximum, and minimum Cp) and estimated mean extreme Cp are analyzed. Two methods are used to obtain the estimated mean hourly extreme pressure coefficients. For the first case, the uncertainties according to repeatability, model-building, use of different wind tunnels, and estimation techniques for pressure coefficients statistics (i.e., both observed statistics and estimated mean extreme Cp) were estimated. For the second case, the pressure coefficients statistics (i.e., both observed statistics and estimated mean extreme Cp) of model and full-scale records achieved for a comparison. Individual tap time series as well as the area average and moving average time series were used to establish the uncertainties. The best-fit (Palisade Corporation, 1993) program is used to obtain best-fit probability density function and summary statistics for the error terms of all observed statistics comparison.Show more