Multinomial Model
Feature selection and dimension reduction for single cell RNA Seq based on a multinomial model
... the multinomial dis- tribution. The multinomial model adequately describes negative control data, and there is no need to model zero ...
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Social and demographic factors associated with morbidities in young children in Egypt: a Bayesian geo-additive semi-parametric multinomial model
... Covariates. We considered the following socio-demographic factors as explanatory vari- ables: child’s age, sex, body mass index (BMI), maternal age at first birth, place of residence, household size, and mother ’ s ...
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Social and demographic factors associated with morbidities in young children in Egypt: A Bayesian geo additive semi parametric multinomial model
... Covariates. We considered the following socio-demographic factors as explanatory vari- ables: child’s age, sex, body mass index (BMI), maternal age at first birth, place of residence, household size, and mother ’ s ...
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Distracted multinomial model for corona screening at entry ports
... distracted multinomial model to refine the imprecise corona screening process and interpret the probability of detecting a corona case in US entry ...
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Small area estimation of labour force indicators under a multinomial model with correlated time and area effects
... the multinomial outcomes for males and females from the same county might be ...proposed Model 2 and Model 3 have not separate fixed effects for males and females and so essentially handle this ...
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MNP: R Package for Fitting the Multinomial Probit Model
... the multinomial model. The word “choices” is used because the model is often used to describe how individuals choose among a number of alternatives, ...the model reduces to the standard ...
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A coarsened multinomial regression model for perinatal mother to child transmission of HIV
... coarsened multinomial model using the Expectation Maximization ...coarsened multinomial model then lay out strategies to adjust for ...
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Modelling Choice of Credit by Small Scale Entrepreneures’ in Oyo State, Nigeria: An Application of Multinomial Logit Model
... while multinomial model was used to analyze the ...estimated multinomial logit model with personal savings as chosen base are that: entrepreneurial choice of credit from various sources ...
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implicit-moral-evaluations-a-multinomial-modeling-approach.pdf
... corresponding multinomial model, finding that Intentional Judgment was sensitive to time pressure whereas Unintentional Judgment was not reducible to negative ...
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Multinomial logit bias reduction via Poisson log linear model
... The multinomial logit model (1) and the Poisson log-linear model (2) are both full expo- nential families, and so in either case the bias-reducing penalty of Firth (1993) to the likelihood is simply ...
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Bayesian Multinomial Logistic Regression for Author Identification
... on multinomial or polytomous generalizations of logistic ...a multinomial logistic regression model allows us to combine training data with prior domain ...
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MULTINOMIAL LOGIT MODEL ESTIMATION OF HOUSEHOLD CHARACTERISTICS INFLUENCING CAR OWNERSHIP IN AKURE, SOUTH WEST, NIGERIA
... Data obtained from different zones based on land use were coded, imputed and analysed in SPSS 22 environment. SPSS 22 is a software package used for statistical analysis. SPSS is among the most widely used programs for ...
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Variational Multinomial Logit Gaussian Process
... the multinomial probit used by Girolami and Rogers ...a model with the threshold likelihood function and prior covariance function k x (x,x ′ ) + δ (x,x ′ ), where δ is the Kronecker delta function, is ...
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Multinomial Logit Models with Implicit Variable Selection
... techniques. One of the oldest penalization techniques is ridge regression which was extended to generalized linear models (GLM) by Nyquist (1991), Segerstedt (1992). In contrast to ridge regression which shrinks the ...
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Nonparametric identification of static multinomial choice models
... The next section presents a stylized version of the multiple choice model and the Theorem 2 as stated in Matzkin (1993). The following section revise the assumptions and prove a new theorem to achieve the ...
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A Multinomial Theorem for Hermite Polynomials and Financial Applications
... The aim of this paper is to derive a theoretical framework that underlies many usages of Hermite polynomials in finance. In particular, the first main result of this paper is to have established a link between the ...
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Characterizations of multinomial distributions based on conditional distributions
... In Section 3 a characterization of the joint multinomial of two identically distributed random vectors based on one conditional multinomial... distribution is given.[r] ...
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Multinomial-Sampling Models for Random Genetic Drift
... Here, we extend our investigation of a monoecious population to a dioecious one. First, we shall deduce our model from population regulation and establish that it ne[r] ...
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A sparse multinomial probit model for classification
... probit model – a generalized linear model with a normal ...this model can be expressed as a latent variable model that closely resembles the conventional linear regression model and ...
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Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics
... Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics ...The model can also deduce the impact of a treatment and be used for ...the model evidence. We applied ...
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