Multinomial regression
Deep Dirichlet Multinomial Regression
... Dirichlet Multinomial Regression (DMR) and other supervised topic models can in- corporate arbitrary document-level features to inform topic ...Dirichlet Multinomial Regression (dDMR), a ...
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A coarsened multinomial regression model for perinatal mother to child transmission of HIV
... coarsened multinomial regression model for analyzing PMTCT of HIV that accommodates missing and off-schedule test data and allows the effect of treat- ment to depend upon ...
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Permuted and Augmented Stick-Breaking Bayesian Multinomial Regression
... transforms multinomial regression into regression analysis of stick-specific binary random variables that are mu- tually independent given their covariate-dependent stick success probabilities, which ...
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PRIVATE FIXED INVESTMENT BEHAVIOUR OF ZIMBABWE’S MANUFACTURING FIRMS: A MULTINOMIAL REGRESSION APPROACH
... from multinomial regression indicates that liquidity constraints, credit constraints and the level of competitiveness influence manufacturing firms decisions to invest relative rather not investing given ...
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Socio-economic determinants in selecting childhood diarrhoea treatment options in Sub-Saharan Africa: A multilevel model
... multilevel multinomial regression models indicate that, with all other factors being held constant, living in highly socio-economically disadvantaged neighbourhood is associated with less likelihood of ...
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Who Adopts Agroforestry in a Subsistence Economy?
... Logistic regression model is the best fit when the outcome (dependent) variables are unordered and ...(binary regression model) is the best ...chose Multinomial Regression Model (MRM) for our ...
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Extreme sparse multinomial logistic regression : a fast and robust framework for hyperspectral image classification
... For efficiency, the input weights and the bias between the input layer and the hidden layer of the ELM are randomly generated. It has been proved to be a fast and good data representation method [30–32]. In fact, besides ...
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Statistical Methods for Human Microbiome Data Analysis
... Dirichlet-multinomial regression (SDMR) model was developed to link the microbiome composition to environmental covariates and to select the most important covariates and their affected ...
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Gene Prediction Using Multinomial Probit Regression with Bayesian Gene Selection
... a multinomial regression model (probit re- gressor) with data augmentation to turn the multinomial problem into a sequence of smoothing problems ...all regression equations to constitute a ...
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Comparison of the accuracy of beta-binomial, multinomial, dirichlet-multinomial, and ordinal regression in modelling quality of life data
... that multinomial and dirichlet-multinomial regression models in lower percentages for selecting training set, show weaker performance than other ...the multinomial and ...
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Inference in the Presence of Likelihood Monotonicity for Polytomous and Logistic Regression
... a multinomial regression problem that features nuisance para- meters estimated at infinity to a similar problem in which all nuisance parameters have finite estimates; this conversion is such that the ...
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Multinomial Least Angle Regression with Application to Web Personalization
... Abstract —Keerthi and Shevade (2007) proposed an efficient algorithm for constructing an approximate LARS solution path for logistic regression as a function of the regulariza- tion parameter. In this paper we ...
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Regional differences in unmet need for contraception in Kenya: insights from survey data
... A one unit increase in education among women with primary education in the high unmet need zone increased the multinomial log odds of experiencing unmet need for spacing by 0.45 relative to women with no unmet ...
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Application of Multinomial Logistic to Smallholder Farmers’ Market Participation in Northern Ghana
... logistic regression is used to forecast the probability of category membership on a dependent variable among multiple independent variables which may either be dichotomous or continuous - interval or ratio in ...
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Using homicide data to assist murder investigations
... The first column of Table 17 shows the value of L obtained using the simple frequency approach outlined above. The second column shows L for each of the offender characteristics fitted using the statistical modelling ...
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Driver's Good Postures Correction Model while Driving for Smart Vehicle Seat using Multinomial Logistic Regression
... using multinomial logistic ...using multinomial logistic ...logistic regression models, first, we collected the piezoelectric values from 55 drivers and 17 types of cars from the system, second, ...
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Challenges and Prospects of Commercial Bank Loan Extended to Farmers in Lagelu Local Government of Oyo State, Nigeria
... Contribution/ Originality: This study contributes in the existing literature by investigating the challenges and prospects of commercial bank loan extended to farmers in Nigeria. The study make used of two methodologies ...
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Oral health related quality of life in pregnant and post partum women in two social network domains; predominantly home-based and work-based networks.
... behaviors. Multinomial logistic regression was performed to obtain OR of relationships between occupational contexts, affectionate support and positive social interaction on the one hand, and oral health ...
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Perception and adaptation models of climate change by the rural people of lake Tana Sub-Basin, Ethiopia
... Depending on the assumed distribution that the ran- dom term follows several qualitative choices, models such as linear probability, logit/probit, model could be estimated (Glwadys 2009). In LTSB, we assumed that several ...
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A Model-Based Statistical Classification Analysis for Karamattepe Arrowheads
... Other. Multinomial-LOGIT was performed in IBM SPSS 24 with the NOMREG com- ...the regression model, due to their high cor- relation coefficient (ρ = ...
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