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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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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5 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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13 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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18 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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8 views

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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18 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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28 views

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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21 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
23 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
24 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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42 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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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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35 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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35 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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15 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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36 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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65 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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9 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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5 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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27 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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14 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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13 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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31 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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70 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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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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27 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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69 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 ...
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249 views

Can a Multinomial(1/n, …, 1/n) be characterized as a discretized Dirichlet(1, .., 1)?

So this question is slightly messy, but I'll include colourful graphs to make up for that! First the Background then the Question(s). Background Say you have a $n$-dimensional multinomial ...
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1answer
92 views

How to assess if a model is good in multinomial logistic regression?

I have some ordinal response $y$ that I modeled using both ordinal logistic regression and multinomial logistic regression (to avoid the proportional odds assumption), using two continuous variables ...
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32 views

Advice for test on categorical variables

I am working with two variables - variable 'A' is an independent categorical variable and has three levels 'a' 'b' and 'c'; variable 'B' is continuous response variable data I have classified into ...
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24 views

Multinomial models in R with non-varying alternative values

I have a revealed preference data set on where people travel to do certain activities. I have individual variables for each person/trip, and alternative specific variables for each possible choice ...
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Modelling sub-categories of independent variables

Hello: I have a data set that looks below. I'm trying to model membership in a cluster (3 categories) as a function of various categorical and numeric predictors. The real predictors of interest are ...
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32 views

How to specify reference category for binary independent variables in multinomial logistic regression in SPSS

I am using multinomial logistic regression in SPSS 20, with a DV with three ordinal categories, the last specified as the reference category. I have a mix of binary and ordinal IVs. I have no trouble ...
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76 views

Sample size for categorical data

I have a population of phone calls - 200,000. There are different reasons for each call, but lets assume the number of reasons is known. i.e. 7 different call reasons: 1) Check on order 2) Cancel ...
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68 views

Multinomial logit with aggregate data

I am asking a general question here. Can multi-nomial model be applied to aggregate data. If so , can you give me a reference list.
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1answer
112 views

RJAGS Multinomial-Dirichlet – Observed node inconsistent with unobserved parents at initialization

I am trying to model a simple 2x2 contingency table with a multinomial-Dirichlet model. A snippet of my data z[i,1:4] look like this: ...
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35 views

Estimating parameters of Dirichlet distribution

This is a very basic question but after reading few documents I found online I am a bit confused about Dirichlet parameter estimation. My data is multinomial. I have my Dirichlet prior and I would ...
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89 views

How can I run ordered logistic regression on a large sparse matrix in R

I have a sparse matrix X, 970283x9511, with 970283 documents and 9511 features. I have a vector y of length 970283 corresponding to a rating 1-5. I know of the glmnet package, which has binomial and ...
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63 views

preferential multinomial model (with memory)

I am modeling a system that is like having a container of an infinite number of colored balls. On each day $t$, I pull out a new set of $n_t$ balls and I count the number of balls that are red, green, ...
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33 views

Variance of multinomial distribution that is product of 4 Beta random variables

I have a system of 4 binary random variables, $A$, $B$, $C$ and $D$. $A$, $B$ and $C$ are conditionally independent given $D$, and I'll call one set of samples $ABCD$ an event (e.g. $ABCD$ meaning all ...
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Is quantile multinormal distribution same as negative multinormal disribution?

May I know whether the quantile multinormal distribution is the same as negative multinormal distribution? If not, may I ask what the quantile multinormal distribution function look like? Thank you ...
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For which data can propensity score matching be applied?

I wondered if besides controlled experiments (random distribution of treatments) and observational studies (treatment for homogeneous individuals), other settings apply for propensity score matching. ...
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29 views

sklearn - Multinomial Naive Bayes (data too big???!!!)

I wanted to really understand the rationale behind the following code as written in python sklearn's manual partial_fit(X, y, classes=None, sample_weight=None) when the data is too big to fit in ...
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40 views

Nonlinearity in OLS-models

I have a question connected to the OLS-Model's assumption of Linearity between parameters. What should be done if the assumption is not fulfilled? My second question is if I can use multinomial ...
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26 views

Feasible Multinomial Logit with large number of fixed effects

Is there a way to run something similar to a multinomial logit model with a large number of fixed effects that converges in a reasonable amount of time (I am using Stata)?
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Wald interval for ratio of multinomial parameters

In a trinomial distribution with parameters $p_1, p_2$ I am interested in the parameter $\theta=\frac{p_1}{p_2}$. I would like to find the Wald confidence interval for this parameter, but I think that ...
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Is selection/sample bias immediately caused when I don't exclude data?

I'm running a multinomial logistic regression on 8 independent variables for 180 observations in Stata (version 11). The dependent variable is categorical with 7 outcome categories, categories 1-6 ...