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Questions tagged [multinomial-probit]

The multinomial probit is an extension of the probit regression. The dependent variable can take on 3 or more unordered values. The modell does not have to fulfill the IIA Assumption.

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Conditional Logistic Regression in R

As my first question addressing this matter was incomplete and unclear, I made another attempt with an improved outline. I am currently working on a project in which I have a data-set of the following ...
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Predicted Probabilities in Multinomial Probit Model

I am trying to compute predicted probabilities from a multinomial probit model. Researching the internet has given me two ways how this can be done. The first one is basically just applying the ...
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The Hessian of multinomial Probit model

I wanted to implement multinomial probit in Bayesian with random-walk Metropolis Hasting. To achieve the best numerical efficiency when drawing $\beta$, I need to use the hessian matrix of $\beta$. ...
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Poisson or Multinomial Logistic Regression (or something else)?

There seems to be a lot of discussion about this on CV but none quite answer my question. I have a variable y which represents number of adverse events occurring ...
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Estimation of Demand and Substitution in Case of Multinomial Logit Model

In MNL model, given the different alternative choices, we estimate the probability of choice across different options. E.g. using the fishing data, we can use the following calculations to estimate ...
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What is an intuitive way to understand an ROC curve for a multinomial classifier?

When drawing an ROC curve for a binary classifier, we vary, say the probability threshold of one class vs the other and get the curve. However I'm confused what this means in a multinomial case where ...
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610 views

How to use multinomial probit coefficients to predict?

I fitted a multinomial probit model with one independent categorical variable Y (levels 1,2,3) and two explanatory variables X1 and X2. Using mlogit package in R like this: ...
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Multivariate multinomial probit

I would like to jointly estimate 4 variables. Two of them are categorical and the two others are binary. So I thought about a "multivariate multinomial probit model", but did not find much. What ...
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Is a win-lose model for three Presidential primary candidates appropriate? Multinomial Logit model?

I have a dataset where each record represents a collection of variables for each of the counties in New York. Five variables represent the number of tweets in that geographic area for each candidate ...
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Discrete choice models; estimating probability of new alternatives

Let's say the set of alternatives are $j=1,2,...J$, where $X_i$ is the vector of subject-specific attributes for subject $i$, and $Z_{ij}$ is the vector of alternative-specific attributes for ...
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Deciding between Probit and Multi-nominal Probit if one of three categories is very unlikely? Proving randomness of that category?

I have a choice variable, which is either A or B or C. But apparently C is hardly chosen. And for me it seems like it more "happens to be chosen". I want to estimate which some continuous covariates, ...
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Solution verification - calculation of second derivatives of multinomial probit log-likelihood function

The initial function of log-likelihood of multinomial probit model with $J$ alternatives: $ ln \ell=\sum_{i=1}^N\sum_{j=1}^{J-1} y_{ij} \cdot ln \Phi(\sum_{k=1}^Kx_{ik}\beta_{kj})+ ({n_i-\sum_{j=1}^{...
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Difference between multinomial logit and multinomial probit

Similarly to the question Difference between logit and probit models I am wondering what is the difference between a multinomial logit and a multinomial probit. And when should I apply which of the ...