A multivariate, discrete probability distribution used to describe the results of a random experiment where each of $n$ outcomes are placed into one of $k$ nominal categories.

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Analytical Formula for Exceedance Correlation of Multivariate Normal Distribution and others

I understand that the Exceedance Correlation concept. Knowing that the multivariate normal distribution has asymptotic independence on the tail, lower and lower exceedance correlation approaching to 0 ...
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16 views

Multinomial response with repeated measures

I'm studying how sex influences habitat use. I'm looking for suggestions on how to analyze a repeated measure design with a multinomial response variable. I should note that the number of repeated ...
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1answer
21 views

Sample Size Determination for Multinomial Proportions

I have a number of samples of different sizes from a population of unknown size. The data are market shares for five different products within a category (so they sum to 1). I want to know how many ...
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43 views

Multinomial Logistic Loss vs (Cross Entropy vs Square Error)

I observed that Caffe (a deep learning framework) used the Softmax Loss Layer SoftmaxWithLoss as output layer for most of the model samples. As far as I know, ...
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29 views

Reasonable approach for modelling churn (survival) and choice of intervention campaign (multinomial regression)?

I've only recently moved into customer analytics, and would love to get some advice around designing a reasonable approach to modelling my data. I want to be able to predict customer churn (that is, ...
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29 views

Residual deviance difference between multinom() and vglm() function

I have used two functions multinom() in package nnet and vglm() in package (VGAM) to make a multinomial logistic regression. ...
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1answer
24 views

Multinomial regression interpretation SPSS [duplicate]

-- start reading from the edited part -- When running a multinomial regression the two values we are really interested in are the values 'B' and B(Exp)'. Let's say we have (fictive numbers): B: ...
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coding for multinomial logistic regression dv

I have run a multinomial logistic regression. One of the 3 IVs is categorical and has 5 levels and the one DV is categorical and has 6 levels. I coded the levels from 1-5 for the IV and 1-6 for the ...
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13 views

Visualizing multi-class ROC analysis [duplicate]

I am running a multinomial logistic regression model (with 3 possible outcomes) in R. I am trying to find the best way to assess the predictive power/accuracy of the model, and the best thing I've ...
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12 views

Multinomial logistic regression, how to treat conditions without variance?

Currently I need to conduct a multinomial logistic regression, but my output shows an error message and incomplete results. I expect this is due to the fact that in one of my conditions, all ...
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1answer
152 views

Name of single sample multinomial distribution

The Binomial$(n, p)$ distribution is called "Bernoulli distribution" with parameter $p$ in the special case $n=1$. Many properties of the Binomial are derived from the fact that the sum of $n$ i.i.d. ...
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R: Multinomial Logistic Regression for health data

I am doing some data analysis on a fairly large health data set of patients with diagnoses and the respective procedures received for each event. I was asked to run a multinomial logistic regression ...
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18 views

Interpretation of year interaction terms

I am currently specifying a multinomial logit model estimating labour market transition probabilities using quarterly survey data. I have two specific explanatory covariates that I am particularly ...
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1answer
22 views

Exogenous weighting: multinomial logit models

Can the utilities or choice probabilities be weighted by population weights? Or must the weighting actually occur at the observational/individual level? I assume it must occur at the observational ...
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1answer
23 views

How to assess the relationship between a continuous explanatory and categorical response variable?

I have a categorical variable as my response variable (severity of disease: absent, mild, mild/moderate, moderate, moderate/severe, severe), and I have a continuous variable (test scores, which are ...
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1answer
23 views

How to test for significant differences between 3 groups of 5 dimensional polytomous data

I have asked participants in a study to categorize the meaning of messages across 5-dimensions pertaining to Happiness, Sadness, Sarcasm, Honesty, and Anger. For each dimension there were 5 potential ...
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20 views

Simplification of the marginalized multinomial distribution

The likelihood expression for multinomial count variables $\{n_1, \dots, n_K\}, \sum_{k=1}^K {n_k} = N$, conditionned by parameters $\{\pi_1, \dots, \pi_K\}, \sum_{k=1}^K {\pi_k} = 1$ is given as: ...
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17 views

Multi-label multinomial logistic regression

I have stock data with about 50000 features and 20 labels. Each of the label can take one of three values: -1, 0, 1. I've divided the data in 9:1 ratio so that nine tenth of the data is used to ...
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Are multinomial logits modelled by multinom() in {nnet} robust to the linearity assumption?

I am modelling a multinomial logit using the multinom() function in the nnet package: fit <- multinom(outcome ~ gender + age, data) However, it looks like the linearity of the logit ...
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20 views

Using {rms} package for multinomial logit

Is it possible to use the rms package to model multinomials logits, or elsewise to model several binary logits to achieve the same effect? I am aware that there are many other packages specifically ...
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Alternative to multinomial logistic regression for model with multiple related outcomes

I have been using multinomial logistic regression to answer a question analagous to: "which candidate will a person vote for, given particular demographic characteristics?". I am now looking to move ...
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16 views

Could someone outline the pros and cons of the mlogit{mlogit} versus the multinom{nnet} functions for modelling multinomial logistic regressions in R?

I am trying to make an informed decision about which of the mlogit and multinom functions, in the mlogt and nnet packages respectively, I should use for a multinomial logistic regression model. I do ...
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29 views

Need serious help preparing a GLMM and multinomial logit model in R

I am having trouble choosing appropriate statistical packages in R, in order to analyze (1) the relationship between a binary response variable and a few categorical variables which may be nested ...
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25 views

Cell count distribution assumption in loglinear modelling

In relation to loglinear analysis, SPSS gives two options for "Distribution of Cell Counts". The SPSS User Manual states: Assumptions. Two distributions are available in General Loglinear ...
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SAS: any way to configure individual effects in multinomial logistic regression?

We use proc logistic to fit a multinomial logistic regression, and the link function we chose is link=glogit. Given the multinomial nature, one variable would have effects cross multiple segments. We ...
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23 views

Prediction of the probabilities in the stochastic process

The system can have n different states. At every time period it might either stay in the previous state or move to another state due to two possible reasons (A and B). I need to predict three ...
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Multinomial Logistic Regression: Redundant Parameter

I'm running a Multinomial Logistic Regression in SPSS Version 22. The Dependent variable is CameraBrand (options are B, R, or Field - B and R are observations made from the two camera brands, Field is ...
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22 views

Multinomial Logistic Question

Using PROC Logistic with the glogit link, I am attempting to classify records according to 1 of 3 responses (0, 1-2, 3+). After cleaning and running multiple models, I landed on what I thought was a ...
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1answer
37 views

Running Latent Dirichlet Allocation (LDA) on word counts

I have difficulties understanding the VB implementation lda-c. In particular, the method expects as input a bag-of-words representation of documents, where distinct words appearing in a document are ...
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1answer
32 views

normalization constant for categorical distribution as exponential family

Let r.v. $X$ has categorical distribution. We can represent its pmf as $f(x\mid\vec{p})=\Pi_{i=1}^{K}p_i^{I[x=i]}=\exp[\sum_{i=1}^{K}I[x=i]\ln p_i]$, there is no explicit normalization constant ...
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62 views

Degrees of freedom for chi-squared test for a random variable potentially from a mixture generation

I recently posted Multinomial mixture model but got no answer. Hence I take the liberty to present what I came up with on my own and a follow up question: I have two processes which generate a series ...
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32 views
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39 views

Multinomial mixture model

Dear StackExchange Community I'm looking for a package or an elegant way to solve the following question with R: I have two processes which produce a number of A, C, G, T's following a multinomial ...
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38 views

Variance of binomial vs. multinomial distribution in cross-validation

Suppose we have a dataset with $N=100$ observations. We do $K$-fold cross-validation with $K=10$ and $K=100$. In the first case, the classification decisions are sampled (can I say it like this?) ...
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1answer
38 views

Multinomial distribution - where is the normalising constant?

I've been reading up on Multinomial/Dirichlet priors and came across this note. I'm wondering why the normalising constant for the multinomial distribution drops out in the derivation of the joint ...
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31 views

Predicting penalized multinomial logit in R (pmlr package)

I am using the pmlr package to estimate a penalized multinomial logit model, as in the example below: ...
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51 views

deal with interaction that is composed of correlated variables in multinomial logistic regression

I'm trying to build a model between three variables: y=user interest, x1=time, and x2=space. All the three variables are categorical, with the response variable y=user interest being described by ...
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1answer
90 views

Principal component analysis / multinomial logistic regression

I'm trying to see how level of scepticism impacts willingness to change diet. To measure sceptism I've used a 7 point likert scale. The study I'm basing my research on used a principal components ...
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14 views

Alpha Parameter Specification Dirichlet Prior

I have a straightforward Dirichlet-Multinomial model with code that is running in RJAGS. The data are a collection of 200 2 x 2 contingency tables. The multinomial counts are those of a 2 x 2 ...
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6 views

Multinomial naive bayes explicit features

What is the difference between naive bayes nad multinomial naive bayes? What are thre three prime differences and/or features?
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35 views

VIF around 3.5 in two covariates, how shall I deal the problem?

in my multinomial logistic regression model (sample size n=290) I am adjusting the results for a group of covariates (n=8). I tested them for multicollinearity and if most of them have a VIF lower ...
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15 views

Multinomial logistic regression and interaction [duplicate]

I am running a multinomial logistic regression and have my final model, but now want to check for interactions between my two exposure variables and my independent variables. When I run this, one of ...
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23 views

How to calculate non centrality parameter?

Suppose $Y\sim N_p(\mu,\sigma^2I_p)$. Let $A$ be a symmetric idempotent matrix. I want to show $Y^{T}AY$ follows a chi-sq distribution with some non centrality parameter. Suppose ...
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37 views

Can you use a single set of weights for all classes in logistic regression?

For this question I want to specifically focus on the the method in this tutorial: CRF tutorial See equations 1.6 and 1.7 $p(y|\boldsymbol{x}) = \frac{\exp\left \{{\lambda_{y} + \sum\limits_{j=1}^K ...
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22 views

Uncertain about research strategy

I am currently busy with defining my methodology/research design. What I am trying to research is why consumers avoid the first retailer (the cheapest retailer in the shopbot) and what factors drive ...
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1answer
108 views

Expectation-Maximization Algorithm for Binomial

I have a multinomial distribution with four outcomes, with a pdf: $$p(x_1,x_2,x_3,x_4)=\frac{n!}{x_1!x_2!x_3!x_4!}p_1^{x_1}p_2^{x_2}p_3^{x_3}p_4^{x_4}, \sum_{i=1}^4x_i=n, \sum_{i=1}^4p_i=1$$ The ...
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16 views

Learning over Multinomial data

I have a training data with 68 features... Each of which is a different multinomial distribution. Eg. Feature 1 can take 1 of 4 values while feature 2 can take one of 10 values. Which classifier or ...
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32 views

Show Pearson Chi-Square Statistic is Score Statistic for Multinomial Data

I've read in many textbooks that the Pearson Chi-Square statistic is a score statistic in the multinomial setting (as well as others). I thought it would be a good exercise to derive this, but I am ...
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89 views

Help setting up pymc to solve this problem relating to distribution of colors in M&M's

My overall goal is to work through the "Bayesian Methods for Hackers" book. So far I understand how to do simple things with pymc (like determining the parameters for a linear model and for a ...