Questions tagged [discrete-data]

Refers to data generated from a distribution that has a countable sample space. Discrete data may be nominal (e.g. the distribution of race in a sample of individuals) or ordinal (e.g. the number of errors on a page of text).

145 questions
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How can I test whether an empirical discrete distribution is symmetric?

For example, I have a distribution with mean = 55.46; med = 54.5; mode = 45. The Shapiro-Wilk is non significant, the data are unimodal, and there is no significant skew or kurtosis. At a glance, the ...
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Estimating a probability distribution with a discrete and continuous part

This is a question more for advice and a suggested starting point than anything else (though anything else is cool as well ) The data that I have is something like this - 1,000,000 data points of ...
342 views

Application of likelihood ratio test to test the Markov property

Do you know a reference (freely available on the web) where the likelihood ratio test is applied in order to test for the Markov property? The setting is a directly observable discrete Markov-chain ...
91 views

How to model the distribution of a word game in order to find correlation between demographics and chosen words

I have an experiment (in the form of a word game) whereby people are asked to choose a set of words to describe associations with a topic with the aim of having another person guess the topic. I ...
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How to define and model consumption bundles?

Imagine an a la carte buffet with n different rooms. On entering the buffet you pick a room (let's say American, Mexican or Italian food) where you stay for the duration of your visit. Once in a room,...
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Stopping rule for chi-squared discretization algorithm

I developed an algorithm that uses the chi-squared test to perform supervised discretization of a continuous variable. I described it in the paper "ChiD-A Chi-Squared Discretization Algorithm" ...
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Fit data based on generating function

Suppose I have iid data generated from a discrete random variable $X_i \sim D(\lambda)$, and I would like to infer the parameter $\lambda$. Unfortunately, I do not know the likelihood function for $D$,...
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Representation of Noise in Fourier transform

I perform an experiment where I sample $M(k)$ which is in theory related to $|f(x)|^2$ via $M(k)=\int e^{ikx}|f(x)|^2\,dx$. I perform the discrete FT on my data in order to obtain $|f(x)|^2$. Without ...
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Goodness-of-fit for Discrete Distributions

I've been doing some data analysis with Scipy. So far I accomplished this with continuous distributions: I can fit a probability distribution to a set of data points using a maximum likelihood fit. ...
108 views

Discrete Choice Models

For multinomial (or mixed) logit models, when the choice set is too large, either strategic sampling or random sampling of the choice set can be used. My question is: Is that also true for panel data ...
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Detrending Discrete Data

I am trying to detrend some discrete data and I am having difficulty finding a model to describe the trend. There is a number of discrete data points and there is a linear error being introduced with ...
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Quantifying differences in a discrete distribution across several populations

Suppose you have a discrete random variable, $Y$, with a large number (say, $300$) of discrete (which happen to be nominal) possible outcomes. The mass function, $p(y)=P(Y=y)$, is unknown but a sample ...
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Books for mixed distributions (continuous and discrete)?

What is a good book that covers mixed distributions? Most statistics books either only briefly mention them or do not cover the topic at all. I'd like to have a comprehensive resource covering ...
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Averaged continuous Kernel Density Estimates in lieu of a discrete Kernel Density Estimate in Monte Carlo Proceedure

I am thinking of using this code in a Monte Carlo routine to generate Kernel Density Estimates for subsequent use in a Naive Bayes Classifier (see this earlier post). The author of the code states ...
I have multiple Bayesian network models, each producing some estimate or inference about a variable $PW_2$, which is given by $P_1(W_2|W_1)$ in one model and $P_2(W_2|W3)$ in the other, but I want ...