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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glmnet: How to make sense of multinomial parameterization?

Following problem: I want to predict a categorical response variable with one (or more) categorical variables using glmnet(). However, I cannot make sense of the output glmnet gives me. Ok, first ...
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10 views

multinomial logistic regression with transition period

given data that has to periods t0 and t1 and in each period there are two categories that a subject can be in {a,b} would there be an inference problem to formulate a multinomial logistic model as ...
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1answer
48 views

“Better fit” using aggregated data in comparison to disaggregated data: explanation?

I have fitted multionomial regression models to two different datasets, but from the same country, corresponding to the same event. Dataset A is an aggregated dataset (at country level), relating a ...
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15 views

Diagnostics for multinomial and ordinal regression models

In the case of a binary outcome and a number of explanatory variables, logistic regression can be used and a number of diagnostic tools can be applied to assess the relative (e.g. AIC, if one wishes ...
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1answer
31 views

Reason for Correctly Classified Percentage of Multinomial less than 70%

Does anyone of you know why is the correctly classified percentage of multinomial less than 70%? The minimum requirement to be a good model is 70% but my result show less than this. Anyone know the ...
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19 views

transform multinomial variable to continous for testing

Following Glenn comments im editing my question and posting an example: I want to know if my procedure here is valid. We tested the relationship between ecomorph and escape behavior across ten ...
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7 views

Cost keeps on increasing in Multinomial logistic regression, instead of reducing

I am trying to implement multinomail logistic regression using gradient descent, following http://ufldl.stanford.edu/wiki/index.php/Softmax_Regression My data set has 7 ratings classes from 1 to 7. ...
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15 views

selection bias correction based on multinomial logit

Can anyone please explain how to correct selection bias in the Ordinary Least Square model when independent variable (which is expected to have correlation with errors or creating endogeneity problem) ...
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2answers
31 views

How can I use ratios to set priors on multinomial probabilities?

I have a vector, $k$, that determines allocation to five pools. I'd like to set priors on these probabilities, and I can provide informative priors on a few of the ratios, e.g.: $$ \frac{k1}{k2} ...
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1answer
21 views

Draw a multinomial distribution from a Dirichlet distribution?

I have a very rough understanding of the Dirichlet distribution and already seen some visualizations of its pdf over the 2-simplex, i.e., $\alpha$ is a 3D vector. However, I still do not understand ...
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1answer
33 views

JAGS Multinomial mixture model with missing data

I am trying to fit a multinomial mixture model to data from a stream depletion survey. The data were collected by selecting a stream site that is a standard length (usually 150-200m depending on ...
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18 views

Simulation from Dirichlet distribution with WinBUGS

I have a question. Now I am learning WinBUGS, doing bayesian statistics. How, can I simulate a Dirichlet distribution (which is the posterior, for my model ...
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1answer
55 views

Finding multinomial logit regression coefficients in R

I run a multinomial logit regression model for a multiclass classification problem and use the following R function: trainedModel <- multinom(UNS ~ ., data = traindata) Where ...
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22 views

Using multinomial testing with 3 outcomes

I am a little lost on how to do a multinomial testing with 3 outcomes, where i want to calculate the probability of success based on following data: Success: $p^1 ...
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23 views

difficulties evaluating if a ordinal multnomial model fitted with polr (in Rstudio) can be used for predicting over new data

I'm getting very different output when i perform a multinomial ordinal model depending on wether I scale or not my data first. Anyone could tell me why? Here are the results with raw data: ...
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52 views

How to interpret the output of a multinomial classification model in R package gbm

After running a gradient boosted model with n data points using multinomial regression where the response variable (a factor, as required by the gbm function) has ...
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7 views

MNL discrete choice with quasi-SUR 4 equation system, looking for R package that can handle such a system

I am attempting to recreate the model in this paper: Pinjari (2011) in which the author uses a 4 equation system with discrete choice dependent variables in each of the 4 equations. Does anyone ...
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24 views

Single Categorical DV (3 levels), and Single Continuous Repeated Measure IV: which test?

I'm a Ph.D. psych student and am having trouble finding information on which test to use for a continuous repeated measures IV and categorical DV. I would really appreciate some help with this. The ...
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27 views

Am I using Goodman-Kruskal gamma or Somers D or Kendall tau correctly and what do they mean?

I am seemingly blindly following this publication that has done work very similar to what I need to accomplish (page 18-21). My analysis is a multinomial logistic regression where I have 3 possible ...
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1answer
71 views

Interpretation of multinomial logistic regression output from R

I have used mlogit package and I am trying to summarize the results I have from my model. I have a question regarding the reference value and will get to that in a ...
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1answer
40 views

Estimating Multinomial Multilevel Logistic Models by Binomial models

I would like to fit a multinomial multilevel logistic Model. Unfortunately I couldn't find a package that implements this. I tried Stata's ...
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1answer
70 views

Probability of 4 people placed in 3 rooms

A family consisting of four persons—A, B, C, and D—belongs to a medical clinic that always has a doctor at each of stations 1, 2, and 3. During a certain week, each member of the family visits the ...
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1answer
33 views

Correlation between predictor variables in an AIC model

I'm using multinomial logistic regression analysis to analyse deer behavioural responses to camera traps based on 7 predictor variables. I have 2 models which are very close together in AIC value ...
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36 views

piloting a multinomial logistic regression model

I have 11 variables in my data set. farmers Group(1,2,3,4 this is my dependent variable) Independent variables Total holding ,Crop area , barn capacity.....and barn capacity extent match and YPH. ...
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1answer
24 views

Significance test for entropy?

Is there any way to test the difference of entropy given frequency table? For example, let's say we have dice 1 and dice 2, and we experimented with them and they showed up like ...
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15 views

WinBUGS multinomial all parameters are random variables

everyone here. I want to use multinomial distribution, but p[] and N are all random. model is correct and data loaded , model compilied, but it can't still run , it says:value of binomial f[1] must be ...
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10 views

WinBUGS multinomial with unknown parameter and size

I want to use multinomial distribution, but i don't know the p[] and N. So p[] and ...
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27 views

Compute the total variation for multinomial distributions

Suppose I have two discrete random variables, $P$ and $Q$, with probability mass functions given by $p(x)$ and $q(x)$. I know that these random variables are multinomials, generated by choosing $K = ...
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Choosing models with similar AIC values [duplicate]

I'm using a multinomial logistic regression analysis to examine deer behavioural responses to camera traps in terms of 7 predictors (both singly and their interactions). I have found that the model ...
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11 views

Express Multinomial as vector sum of bernoulli trials?

So we know we can think of the binomial as a sum of iid bernoulli. Can we similarly express the multinomial as a vector sum of dependant bernoulli's and get the asymptotic distribution that way? I ...
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2answers
79 views

Differing p values (significant and insignificant) for the same predictor variable in different AIC models

I'm looking at a multinomial logistic regression analysis of deer behavioural responses to camera traps. The levels of the response variable are no reaction, ...
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1answer
37 views

Distribution of (maximum) run length

I am curious about the distribution of (maximum) run length given k independent trials when $p(X=1)=p_1, p(X=2)=p_2, ..., p(X=n)=p_n.$ For example, for a coin tossing for 3 independent trials, ...
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22 views

Discrete Choice Model with Some Levels Combined

I am new to discrete choice modeling, and I am half way through reading Train's Discrete Choice Methods with Simulation. My question is: what do I do if some of the choice levels are combined? For ...
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1answer
47 views

Confidence interval and sample size multinomial probabilities

I'm an absolute beginner in statistics. Please excuse any wrong assumptions or missing information in my question. I have a question that relates to a multinomial distribution (not even 100% sure ...
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2answers
81 views

Multinomial logistic regression with geepack in R

I am working on fitting a GEE model to a multinomial logistic outcome using the R package geepack. My understanding is that the package uses ...
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35 views

Multinomial logistic regression interpretation in R

I have run a multinomial logistic regression test for the interaction between species of deer, days a camera trap was in the field and type of reaction. The model with the best AIC value was: ...
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75 views

R multinomial logistic regression interpretation

I have run a multinomial logistic regression test for the interaction between species of deer, days a camera trap was in the field and type of reaction. The model ...
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0answers
10 views

Using multinomial logit to rank observations

I'm trying to devise a model to rank a number of links according to their popularity. The links refer to upcoming events and job offers, and ideally I'd like to have a reasonably simple model that, ...
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32 views

How to calculate marginal effects for categorical covariates using mlogit in R

I am trying to use the mlogit package in R and have been following the vignette trying to figure out how to get the marginal effects for my data. The example ...
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110 views

gbm R multinomial vs bernoulli

I am using the gbm package to fit a binary variable using several attributes, some numeric and some categorical. Since the output varible was defined as factor I initially did ...
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26 views

Selection bias correction and a multinomial logit

I have a data set for a number of people making 2 decisions - where to live; and how many hours to work. For every observation with a non-zero amount of work, there is an observed wage. I've assigned ...
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50 views

Clarification on interpreting Wald's test and Likelihood ratio tests

I am running multinomial logistic regression analysis on my data. The response variable is the number of calves produced each year (0,1, or 2). I am trying to evaluate the influence of the X ...
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1answer
473 views

Binary or Multinomial Logistic Regression in SPSS: Interpretation and Reference Categories

I am trying to analyze my data using Multinomial Logistic Regression whereby my dependent variable is a clinical outcome (sick vs healthy) and 1 independent variables (Factors) are in several ...
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45 views

multinomial logistic regression with alternative specific variables

I am working on a multinomial logistic regression problem which involves features from the dependent variable. It might be better to describe the problem by using the example in mlogit mlogit manual ...
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1answer
35 views

Multinomial logistic regression low classification rate

I am running a multinomial logistic regression with SPSS and I have encountered a problem (?) with my data. I have a dependent variable (DV) with three categories, five independent variables (IV) as ...
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1answer
71 views

multiple choice data simple logistic regression or multinomial logistic regression

I have a survey question where the respondent can check one choice or two choice maximum. Question looks like this: What is the more important characteristic when you buy chocolate? ...
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1answer
103 views

Logistic / multinomial regression as two / multiple Poisson regressions?

Can we instead of doing logistic or multinomial regression do two or multiple Poisson regressions and then combine Poisson predictions to get probabilistic predictions? If yes, how should we transform ...
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36 views

Updating a Dirichlet distribution with partial data

I've got some categorical data where each observation has multiple attributes, and I want to make a probabilistic model of this using Dirichlet distributions. For example, in the two dimensional case ...
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1answer
17 views

Calculate that at least n number of x values occur from multinomial distribution

Let's say X can take on 5 values X<-1:5 each of the 5 values occur with some probability: ...
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36 views

Better prediction models with polling data?

I've been working on a project on measuring polls' accuracy in complex contexts (more than two candidates) where there are a small number of inaccurate polling data points. I thought it would be the ...