Questions tagged [multinomial]

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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Help and example with svymultinom in R? [closed]

I'm using a large dataset and have run several logistic regressions with svyglm. I am now examining a dependent variable with 3 possible outcomes. I discovered <...
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Adding confidence intervals to multinom predicted values plot r [migrated]

I want to create plots with predicted values and confidence intervals for my multinomial logistic models (multinom function, created with the ...
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Confidence intervals for the probabilities of each outcome in a multinomial [duplicate]

I have a survey that includes questions where you can choose one option from a list. For example: "How often do you go to the supermarket?" ...
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Independence models in sampling 2 way contingency table?

I have just went through a lecture on sampling 2-way contingency table data via multinomial, product multinomial and Poisson sampling. The associated reduced models for each sampling are the ...
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Why is Latent Dirichlet Allocation based on word sequences and not counts?

I assumed that LDA was a bag-of-words approach and that words could be exchanged within a document. However, reviewing more in-depth the Gibbs sampling equations, I noted that the compound Dirichlet-...
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Estimation of CDF in multiple points

Suppose we have a sample $X_1, \ldots, X_n$ of i.i.d. real-valued random variables with an (unknown cumulative) distribution $F$. The goal is to estimate the value of $F$ in multiple points. That is, ...
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Partial dependence plot, GBM multinomial

I'm using gbm package to create a gradient boosting model with multinomial family. I have problems in plotting and interpreting partial dependence plots with this type of models. an example: ...
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Little detail when finding the distribution of joint distribution Poisson r.v.'s, given the sum of these Poisson r.v.'s

My professor did an exercise and I almost understood it entirely, but there's a little detail that I could not understood. This is the exercise: We have 4 Poisson distributed random variables: $N_{11},...
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Difference between multinomial logistic regression and mixed-effects models

I am wondering what is the difference between multinomial regression and mixed-effects models. When should I apply which of the two algorithms? Any pointers to literature where the two are discussed ...
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How to make sense of a mulinomial regression output?

I'm running a multinomial regression with the multinom() function. My three independent variables are ordinal categorical variables coded as follows: ...
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Danger of choosing multinomial logit instead of ordinal logit

(I feel like if you're active here, you've come across my problem before because I've been asking a lot...) I want to run a regression, in the area of credit risk in loans, to predict the outcome of a ...
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Multinomial Probability Model with Correlation between random variables

I'm trying to create a p.m.f. for a Multinomial distribution where the variables are correlated with one another. Let $k$ index the random variables $x$ and their probabilities $p$. There are to be $n$...
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Expected value of the largest item in a multinomial distribution

In this question, I use the notation on wikipedia. Suppose $X=(X_1,\ldots, X_k)$ follows a multinomial distribution with parameter $n,\mathbf p$, where $n$ is the sample size or the number of trials, ...
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is it possible to apply Glove with MultinomialNB?

When I try to do mnb = MultinomialNB() mnb.fit(train_glove_features, train_targ) I get the below error: ValueError: Input X must be non-negative I do ...
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Metropolis-Hastings Discrete Proposal Distribution

I have a Metropolis-Hastings scheme implemented, where I am currently inferring a number of parameters using Gaussian proposal distributions. However, I would now like to assume I don't know the ...
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Emmeans produce negative values for prob 95%CI for multinomial regression

I'm fitting a multinomial logistic regression and I'm getting two issues: ...
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Multinomial logit returns nans in some folds of cross validation

I made this code that uses straified kfolds to split the dataset and fit a multinomial regression, and get the accuracy afterwards. My X is an array of has 19 ...
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What would be the probability distribution to simulate K events randomly assigned to N individuals?

I am trying to randomly simulate a population of $N$ individuals among which a predefined number $K$ of them have an outcome. The trick is that I want to assign different probabilities to the ...
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Alternative to Multinomial Logistic Regression when observations are not independent?

I am dealing with an experimental design with a categorical IV and DV: In a linguistic experiment, I asked speakers to form as many sentences as they could using a limited number of words. They were ...
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Censored multinomial with different, observed censorship pools

In the problem I'm working on, I'm trying to infer the proportions of three types of object $A, B, C$ in a population. I'll use $p_A$, $p_B$, and $p_C$ to refer to the proportions. The data I get to ...
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How to model proportions with a hierarchical structure?

I have thinking about how to model proportions for a problem with hierarchical structure. In the problem, I have observations of users over multiple days, where each observation is a proportion of ...
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Two-dimensional Multinomial distribution and an estimator under the assumption of independence

We have two-dimensional multinomial distribution $Mult(n, p)$, where $p = (p(x, y))_{x \in \mathcal{X}, y \in \mathcal{Y}}$ is a matrix containing probabilities of outcomes of $(X, Y)$: $p(x, y) = P(X=...
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R mlogit package: system is computationally singular: reciprocal condition number

I am trying to analyze a choice experiment for a homework: ...
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Multinomial GLM Pearson residuals

The general formula for Pearson's residual is given by: $$ e_i = \frac{y_i - \hat \mu_i}{\sqrt {V(\hat \mu_i)}} $$ But in the multinomial case, the sum of the squared residual, which is the Pearson ...
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Comparing Begg and Gray method and MCMC for multinomial models

I am looking to build a multinomial model and I am considering using the "Begg and Gray" method: https://cran.r-project.org/web/packages/mlogitBMA/vignettes/conversion.pdf And I am also ...
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probability in mixed multinomial logistic regression

I am using MCMCglmm package in R for my multilevel multinomial logistic regression model. I have a level-1 binary outcome 'Sex', which was coded as 1,2, and a level-1 three category unordered ...
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Multinomial logit model with time

Suppose I have a response variable $Y$ which has categories $1,...,C$ and the data is collected over several years from independent individuals. I'm wondering do I need to make sure $P_1,...,P_C$ does ...
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Random effects in a bayesian multinomial model importance of two different random effects to predictive performance. Best approach?

I have a Bayesian multinomial model like so with two random effects. Y <- A|B|C Y ~ X1 + ... + X5 + (1|RE1) + (1|RE2) I have sigma for RE1 and RE2 for B from A and C from A which informs about the ...
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Feature selection and multidimensional modeling in minimal datasets. R (Multinomial Logistic Regression)

Well, im stuck with a problem with a "small sample size dataset". I used to work with data with n>>p and with models that allow me to build 66-33 train/test datasets to construct and ...
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Does a multinomial regression model make sense for a low frequency?

I have data on job types with 3 different specialities: 100% of jobs have a primary speciality, 77% of jobs have a secondary speciality, and 1.6% of jobs have a tertiary speciality I want to model ...
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Multinomial logistic regression for common outcomes

Under logistic regression, the resulting odds ratios can be approximated and interpreted as risk ratios only if the outcome is rare (as a rule of thumb, less than 10% prevalence). This is sometimes ...
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How to report results from a multinomial logistic regression?

I have run a multinomial logistic regression and am interested in reporting the results in a scientific journal. Would it be alright to include a model summary table with the coefficients, standard ...
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Is a multinomial distribution appropriate for modelling this variable?

I'm currently trying to model subject performance on a learning task (Wisconsin Card Sorting Task) in Rjags. One of the outcome variables is a 3x1 matching matrix. Each row of the matrix corresponds a ...
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Confidence intervals for bootstrapped multinomial proportions: Sison-Glaz?

I read the rules and looked for similar posts, but couldn't find any. New to the platform, so if I missed anything, pardon me. I have started looking into uncertainty quantification and I want to ...
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Rank-ordered data - dealing with increased randomness among lower ranks

What is the best way to analyze rank-ordered data when there are signs that respondents were less diligent/able to assign lower ranks? Is it sufficient to introduce a dummy for lower/earlier ranks ...
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Dirichlet distribution vs Multinomial distribution?

Both Dirichlet and multinomial distributions are distributions over vectors, and both Dirichlet and multinomial distributions are constrained so that all of the elements of these vectors sum to a ...
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Probability of linear separation in a dataset with categorical response

I am simulating datasets to which I fit polytomous logistic regression models. The maximum likelihood estimator of this model is undefined when all categories are linearly separated (and it is quite ...
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Nested Multinomial Logit Estimation

I am trying to estimate a nested multinomial logit model for transportation mode - the decision tree of how consumers choose a travel mode for a trip. One way of estimating the nested multinomial ...
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How to assess geographical representativity of a sub-area?

My geographical zone $A$ is subdivided in $k$ different types of areas: $A_1 + A_2 + \dots{} + A_k = A$. These have been measured on a map with neglictible uncertainty: i.e. for any point on the map, ...
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Interpretation of coefficients from multinomial logistic regression

I have run a multinomial logistic regression model with a four level response variable (walk, bike, bus and car) and two predictor variables being their gender (female/male) and where they live (urban/...
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Algorithm did not converge - Multinomial mixed model (mblogit)

I'm trying to fit a multinomial mixed model with the mclogit package (using the mblogit function). But, as I adjusted the model, I'm receiving the following message and I could't find any info about ...
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Poissonization use for sampling size

I'm interested in using the Poissonization trick to solve the following problem, which I made up: Suppose I have a categorical random variable $X$ taking values $1$, $2$, and $3$, with probability ...
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How to do post-hoc comparisons for multinomial model with emmeans

When doing post-hoc pairwise comparisons for a multinomial model using emmeans package, do I use mode = "latent" or mode = "prob."? I'm interested in understanding if the response variable (with 3 ...
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Is there a probability distribution like the binomial distribution but with continuous rather than binary trial outputs?

I'm using a uniform random variable (0 mean, 1 variance) to generate white noise. Then I'm doing a moving average on those samples. I'm trying to figure out the variance of this output distribution. ...
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Confidence interval for categorical data

I have the following data about companies who respond timely or untimely and another category of the answer: ...
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Significance test for a discrete symmetric ordinal distribution

What are possible extensions to the binomial test for a multinomial distribution? Here is a concrete examples: let's say I have 5 positive and 10 negative outcomes with a one-sided test for the null ...
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How to compute multinomial confidence interval for proportion if some categories have fewer than 5 counts

I want to compute multinomial confidence intervals for proportions, and I was planning to use one of the methodologies listed here. The goodman method [1] is based on approximating a statistic based ...
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Modeling stated preference alternative labels vs alternative characteristic levels

I have data from a stated preference survey in which each respondent answers 3 questions each with 3 alternatives. A status_quo / opt-out alternative is the first option for all questions. The ...
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What model should I use for multiple binary response variables?

Consider many traders j = 1, 2, ..., J who can make the following trading decisions: a) buy, b) sell, c) do nothing since they have not previously bought, or d) do ...

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