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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2
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29 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, ...
0
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17 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 ...
0
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0answers
5 views

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 ...
0
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0answers
11 views

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. ...
0
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0answers
14 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 ...
0
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0answers
32 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 ...
0
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0answers
11 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)?
2
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0answers
20 views

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 ...
1
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0answers
50 views

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 ...
2
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0answers
27 views

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( ...
0
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0answers
5 views

mlogitroc problem with Stata 13 [migrated]

I have a question about the additional module "mlogitroc", which should plot a ROC curve based on a multinomial logistic regression. More in details, at the end of computation the software displays ...
0
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0answers
10 views

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 ...
1
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1answer
19 views

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. ...
1
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0answers
21 views

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 ...
3
votes
0answers
32 views

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). ...
0
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0answers
24 views

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 ...
0
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0answers
8 views

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, ...
0
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0answers
9 views

Calculate elasticities of mixed logit

How do we calculate the dis-aggregate direct elasticity of a random-coefficient logit model?
1
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36 views

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 ...
9
votes
2answers
364 views

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 ...
0
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0answers
14 views

hypothesis of unique elasticity in mlogit()

I am trying to run a nested logit model using mlogit() in R. There is an option un.nest.el, which is "a boolean, if TRUE, the hypothesis of unique elasticity is imposed for nested logit models" (from ...
0
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0answers
19 views

Text classification: combine ngrams with original content?

I have a document classification project where I classify websites in one of ~20 categories based on content. My current process is as follows: Extract plaintext Normalize Tokenize Stem Ngramize ...
3
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0answers
34 views

Characterize this discrete distribution

Suppose we have $k$ buckets, with an infinite number of balls in each bucket. The balls within one bucket are indistinguishable, those between buckets are. We assign to bucket $i$ a probability $p_i$ ...
0
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0answers
16 views

Confidence intervals for multinomial mixed models

I am using the ordinal package in R to create a multinomial mixed model using the clmm2 function. However, I cannot find a way to get confidence intervals for the coefficients; confint() does not work ...
3
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2answers
41 views

“Select All That Apply” — How To Generate a Predictive Model with this Type of Question

For a particular question in a survey, respondents have been asked to select all that apply (i.e. say from a list of books they have read). I'm wondering if anyone knows how I would be able to build ...
0
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1answer
29 views

Modelling ordered data which violates proportional odds assumption

I have a dependent variable which describes how many pounds an individual contributed to a cause. The amount is in whole pounds and out of a maximum of 5 (ie. 0,1,2,3,4,5). I have 2 independent ...
0
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1answer
27 views

vglm: Error in vglm.fitter, due to matrix dimension?

I've looked to other Error in vglm.fitter-related posts but they don't seem (or I cannot) related to this one. This the error I get when running vglm for multinomial regression (classification): ...
0
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0answers
114 views

Choice based conjoint with SPSS

Is it possible to run a Choice Based Conjoint analysis (preferably with also no-choice option) with SPSS? Do I need a particular package for that? if not possible with SPSS is it possible with Stata? ...
0
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0answers
13 views

Complement naive bayes

I would like some help in understanding how does Complement Naive Bayes work. I have googled the paper Complement Naive Bayes I understand that naive bayes works by computing the probability of a ...
0
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0answers
15 views

Multinomial logit model when share of each choice is known for an aggregate area

I've been reading an academic paper where multinomial logit has been used to model railway station choice. It's an aggregate model where the ‎observation unit is postcode area in the Netherlands (each ...
0
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0answers
29 views

Softmax maximum likelihood problem: arbitrary constant

I'm doing a multiclassification with a softmax function. The probability of a sample $j$ belonging to class $k$ is given by the softmax: ...
0
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0answers
53 views

glmnet: which is the reference category or class in multinomial regression?

Following post Why {glmnet} can be calculated parameters for all category? I have 4 categories or classes or responses for y (thus multinomial): cat1, cat2, cat3 and finally no-cat. I want my "no ...
0
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0answers
21 views

R: Error with mlogit Conjoint modelling - system singularity

I am building choice models on a dates about coffee preferences. I have 5 alternatives: Brand, Cup, Price, Certification and Local Community Support. The data looks like this: ...
1
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0answers
74 views

Comparison and testing multinomial coefficients

Straight to the problem I want to test the hypothesis that two coefficients of multinomial regression model are equal between them. For example, considering a model where Y is 3 level categorical ...
0
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0answers
7 views

how do i differentiate between alternative specific and alternative invariants using sas?

Okay so my level of expertise in statistics is fresher/rookie. I am trying to predict the the outcome of categorical choices for a product category y (3 choices or 3 flavors of cereal for example). ...
1
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0answers
41 views

Alternative specific conditional logitstic regression with clustering on in individual in panel data: scientifically and computationally reasonable?

My scientific interest is to calculate the price elasticity for an overall set of products (books) in a panel dataset of observations over a 3 year period and I was wondering whether asclogit ...
0
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0answers
17 views

Aggregation of Individual-Level Multinomial Probabilities in R

I have a multinom (multnomial) logit model in R which predicts the probability that a given individual prospective customer will ...
0
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1answer
45 views

Likely mean of a multinomial distribution with dirichlet prior

I am working to create a Bayesian non-parametric estimate of the mean of a distribution given a distribution of observations. Ultimately I'd like to get to a credibility interval of the likely mean of ...
4
votes
1answer
159 views

Regression model for road accidents data

I want to model road accidents data to identify 1) the major causes of accidents and 2) predictors that can explain the accident severity measured by the passengers injury level (minor, major, fatal). ...
3
votes
1answer
99 views

Can multinomial distribution be simulated by a sequence of binomial draws?

I wonder if single multinomial distribution (I will use the notation from JAGS/WinBUGS, but in fact, this is principial thing rather than of particular language) ...
0
votes
1answer
42 views

Is multinomial the same as multiple binomial?

I wonder, if I write - in JAGS, WinBUGS, or in a paper: x[] ~ dmulti(p[], N) is it the same as if I write: ...
0
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0answers
44 views

Confidence interval on replicates from multinomial distribution with bimodal outcomes

I have a Java model which tracks the numbers of 6 types (A-F) of individuals. I am interested in the distribution of different types of individual across simulations with different parameter values. ...
1
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0answers
64 views

Multinomial logistic regression does not match actual data

I was wondering if someone with experience running multinomial logistic regression could look at my data file and results, and explain why the results turned out the way it did. The background: I've ...
4
votes
1answer
113 views

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 ...
0
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0answers
13 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 ...
2
votes
1answer
71 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 ...
1
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0answers
44 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 ...
-1
votes
1answer
34 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 ...
0
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0answers
24 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 ...