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Showing 1 to 20 of 454 for “"multinomial"”.
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Multinomial Link Models
… for analyzing categorical responses, called multinomial link models. It consists of four classes, namely, mixed-link models that generalize existing multinomial logistic models and their extensions, two-group models that can incorporate the observations with NA or unknown responses, …
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Learning Mixed Multinomial Logit Models
Multinomial logit (MNL) model is widely used to predict the probabilities of different outcomes. However, standard MNL model suffers from several issues, including but not limited to heterogeneous population, the restricted independence of irrelevant alternative (IIA) assumption, insufficient model …
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Questions and conjectures about multinomial coefficients
… paper "On Divisibility Properties of Certain Multinomial Coefficients". First we let {ai} be any sequence (finite or infinite) of positive integers such that i1ai ≤1 . It is clear that n!&sqbl0;na1 &sqbr0;!&sqbl0;na2&sqbr0; !&sqbl0;na3&sqbr0;!&ldots; is an integer because it is a multiple …
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Surveillance of Poisson and Multinomial Processes
… these classifications are readily available. A multinomial cumulative sum (CUSUM) chart is proposed to monitor these types of situations. The multinomial CUSUM chart is evaluated through comparisons of performance with competing control chart methods. This research is a result of joint work with …
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Forecasting housing demand in Terengganu using multinomial logit
Housing demand is defined as the number of homes needed as residence per household. There are 3 types of housing developed in Terengganu which are low medium cost housing, medium cost housing and high cost housing. According to the NAPIC, during the 2nd quarter of 2016, Terengganu recorded the …
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Multinomial Nonparametric Predictive Inference: Selection, Classification and Subcategory Data
… is nonparametric predictive inference (NPI). The multinomial NPI model was recently proposed, which quantifies uncertainty in terms of lower and upper probabilities. It has several advantages, one being the facility to handle multinomial data sets with unknown numbers of possible outcomes. The …
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Robustness of Consistent Loss Functions for Multinomial Outcome Models
… to estimate latent parameters consistently in multinomial outcome models. However, it is sensitive to even a tiny fraction of corruption in the training data. Alternatively, other loss functions in the family of strictly consistent loss functions can be used to consistently estimate model …
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Some aspects of fitting multinomial models in a GLM framework
… least squares algorithm can be used to fit a multinomial regression model, with logit link function or own link functions, with any number of explanatory variables. The responses of each individual can be aggregated and the data can then be represented in a contingency table as are given in …
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An efficient multinomial sampling algorithm for spatially distributed stochastic particle simulations
… This particle-resolved method is based on a multinomial sampling algorithm which calculates the number of particles transferred between adjacent sub-volumes in the domain at each time-step. The particle-resolved method is compared with the traditional finite volume and Monte Carlo methods. …
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Asymptotic simultaneous confidence intervals for the probabilities of a multinomial distribution
… confidence intervals for the probabilities of a multinomial distribution. The approach used is to consider the Chi-square goodness of fit statistic as a function of the population parameters and to invert this function to obtain a set of simultaneous confidence intervals for the parameters The …
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Recent versus lifetime intermetropolitan Brazilian migration: Estimates of a multinomial logistic model
This study examines interregional Brazilian migration in the form of metropolitan migration. The main intents of this are: to verify the effect exerted by a set of would-be migration determinants (explanatory variables) on migration decision, and to compare the responses of migrants, given their …
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A Sentiment Analysis of "Filipinx" on Twitter Using a Multinomial Naïve Bayes Classification Model
<p>On social media, the use of “Filipinx” as a gender neutral, inclusive term for “Filipino” tends to generate high user engagement, at times without regard for the original context in which the word appears. This project applies computational methods to collect a large dataset in English/Filipino …
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Exploring Field Programmable Gate Array Architectures for Pascal's Simplex-based multinomial option pricing
… FPGA architecture for Pascal's Simplex-based multinomial option pricing and presents a detailed comparative analysis of FPGA and CPU implementations. The results show that FPGAs provide substantial performance improvements in terms of speed and scalability, both for European and American style …
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A multinomial modelling of the determinants of child labour in Namibia using the 2018 Namibia labour force survey
… and 5,136 employed children was analysed using a multinomial logistic regression model. Results of the analysis revealed that the child’s residence (urban/rural), region, age, literacy status and educational attainment were all significant determinants of child labour in Namibia. In addition, it …
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Determinants of women’s participation in Namibia ’s labour force: A multinomial analysis of the 2018 Namibia labour force survey
… research study using the 2018 NLFS and a multinomial logistic regression technique. Results revealed that area location, region, age group, marital status, literacy status and education level were significant determinants of employed women’s participation in the labour force in Namibia, …
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Linear and log-linear models based on generalized inverse sampling scheme
… count data. Also negative binomial and negative multinomial (NMn) models are applicable when there is only one rare category in the population. Here, a new model, based on generalized inverse sampling scheme, is introduced to study several rare events simultaneouly. The generalized inverse …
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Analysis of Discrete Data under Order Restrictions
… concepts are extended to deal with independent multinomial populations. Natural orderings such as stochastic ordering and cumulative ratio probability ordering are discussed. Methods are developed for the estimation and testing of differences between binomial as well as multinomial populations …
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Regression Methods for Categorical Dependent Variables: Effects on a Model of Student College Choice
… policies and analyzed with classical linear, multinomial logistic, and ordered logistic regressions. Choice of regression method did not affect overall model performance as evidenced by significant <italic>F</italic> and Likelihood Ratio <italic>χ</italic><super>2</super> tests. The full …
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Bayesian analysis for categorical survey data
… and multivariate categorical survey data. The Multinomial model is used and the following problems are addressed. Limited information about the design variables leads us to model the unknown design variables taking into account the sampling scheme. Random effects are incorporated in the model …
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