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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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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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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Testing whether data follows a binomial distribution vs. multinomial [closed]

I want to test whether my data follow a binomial distribution or multinomial. So the null hypothesis is H0: X follows binomial, Ha: X follows multinomial. I have hard time applying chi-square goodness ...
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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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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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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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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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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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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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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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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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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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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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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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58 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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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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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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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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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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27 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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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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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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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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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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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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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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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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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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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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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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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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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 ...
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Is this a true inequality over multinomial parameters?

Let $p_1,\ldots,p_k$ be the multinomial parameters sampled from a Dirichlet distribution. Assume $\bar{p_1},\ldots,\bar{p}_k$ be the mean of Dirichlet distribution. Then, $$Pr( ...
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Number of parameters in multinomial logistic regression

In Chapter 10 (Directed graphical models) of Murphy's Machine Learning text, the author claims that multinomial logistic regression has $O(K^2 V^2)$ parameters, where $K$ is the number of discrete ...
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Bit Error Rate - Multiple Bernoulli trials with different probabilities

If you transmit a sequence of bits over some line, errors may creep in. For instance, if the Bit Error Rate of this line is 1%, on average, every 1 out of 100 bits will flip to the opposite value. ...
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Propagation of uncertainty: entropy of multinomial

My goal is to estimate the entropy of a multinomial distribution, based on a single observation (a set of counts for each possible outcome). I also want to calculate the uncertainty in my estimated ...
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Student classification with Multinomial Logit

I’m analyzing student performance data. In my dataset, each row corresponds to a student and each column contains several performance metrics (continuous) and the student type (categorical, 4 types). ...
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Distribution of residuals in multinomial / ordinal logistic regression

In simple logistic regression, the standardized residuals are assumed to be normally distributed. Are there any such assumptions for ordinal or multinomial logistic regression? Because in these ...
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Why does the number of samples required decrease when the number of classes increase when calculating sample size for a variable number of answers?

I wanted to post this as a follow up to Varty's excellent response to this question regarding the number of samples required to achieve a given confidence interval with a variable number of answers, ...
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Calculate elasticities of mixed logit

How do we calculate the dis-aggregate direct elasticity of a random-coefficient logit model?
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mixture regression model with networked variables

I am thinking about the following regression model; In my regression model, there is prior information on the regressors that they are connected like a network $T$. The purpose of my regression model ...
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What distribution does Fisher's exact test assume?

In my work I have seen several uses of Fisher's exact test, and I was wondering how well it fits my data. Looking at several sources I understood how to calculate the statistic, but never saw a clear ...