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).

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20 views

Correlations between test question scores with discrete and small number of values

I am a newbie at statistical analysis. I have been using the Pearson correlation coefficient for pairs of test question scores. The test had questions some of which carried 1, some 2 and a few ...
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6 views

Neural Network - Multiple discrete and continious inputs

In order to keep the distance between discrete values irrelevant we often use one-hot encoding feature vectors to normalize our feature vector. So a discrete value could be splitted up into a number n ...
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1answer
18 views

Classification with ordered classes?

Say I want to train a classifier that assigns an image of a person as young, middle-aged, or old. A simple way would be to treat the classes as independent categories and train a classifier. But ...
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1answer
13 views

I have a discrete-valued time series and would like to analyse it, but dont know where to start

Due to some health issues, each day at about the same time, I give myself a score which represents the state of my health: specifically, fatigue, with 1 being the worst and 10 the best. In practice, ...
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1answer
26 views

Lottery machine probability

Assume we have a lottery machine where you press a button and it returns one of 5 motifs in one of 5 colours. Each of these also has a chance to be gilded. Assume I have a dataset containing ...
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1answer
24 views

time is a continuous or discrete variables?

I am trying to create a prediction framework of what a customer will buy on a website, so I am confused if time-connection variable (time of the connection of a customer) is a continuous or discrete ...
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14 views

Picking tuples from a list with low discrepancy

Given a list of m items, I am looking for a way to repeatedly pick a tuple of n distinct items from this list with low discrepancy. For example, suppose I have a list of 3d points, and I want to ...
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13 views

Simple Good-Turing smoothing - probability of unseen if no frequency of 1

I am using the Simple Good-Turing estimation procedure to estimate probabilities for events, some of which have not been seen in the sample. In the procedure, the probability of unseen events is ...
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11 views

Modeling : How do I learn how a discrete function with some smoothness properties evolves over time?

I have a function f over an equi-spaced grid. The function is somewhat smooth, and I can make it smoother (e.g. by doing some type of nearest neighbor averaging), but it will have several peaks and I ...
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1answer
32 views

Performing a t-test with discrete (currency) data

I want to perform a 2 sample t-test assuming unequal variances, however my variable is currency. Currency is discrete, however when checking the assumptions of the t-test, I see that the data should ...
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9 views

Best way to tackle heterogeneity in oncologic models

I need to model the health outcomes from an immuno oncologic treatment to which patients are responding differently depending on their immune condition, which is unknown to the investigator. I was ...
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1answer
30 views

When is time treated as a discrete variable?

Time is usually treated as a continuous variable but in some cases it is discrete. An example would be with a drug study and measurements are taken at 1, 2 and 3 hours. Am I right to think an ...
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1answer
46 views

Prediction Model on categorical y with more than 20 levels

My goal is to predict y, but my dependent variable y has more than 20 levels. I dont think multi-nomial model would be a good ...
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22 views

Two Sample Discrete K-S Test

Recently I got a review for a paper that asked me to show that two probability distributions match. They hinted that I should perform Two Sample K-S test. I know there is a discrete R package dgof to ...
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13 views

How to deal with continuous variables with NULL values in prediction tasks?

I'm currently working on a machine learning project, trying to predict the expected revenue from a specific user. I have a long list of features that display the date when the user first performed a ...
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0answers
11 views

Discrete LRT statistic

So I want to do a hypothesis testing on a parameter of a discrete distribution, I've calculated the LRT $\Lambda(x)$ and I found something with $\prod x_{i}^{x_{i}}$, I couldn't extrat the ...
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34 views

How to fit a discrete distribution that can only be sampled from to count data?

My question is similar to this one. Assume we have a distribution from which we can only sample, but have no information on its pmf and consider further some count data: ...
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1answer
69 views

Measuring how well a new vote fits to a model of existing votes

My knowledge in statistics is very limited, so I hope this is actually an easy question. I am working on a kind of survey application where users either vote between a finite number of discrete ...
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2answers
65 views

Gibbs sampling and mixed distribution

For a project, I need to simulate from a joint distribution with both continuous and discrete variables that are dependent. The conditional distribution of any variable given the rest is known. I ...
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0answers
21 views

Bias of sample correlation for discrete distributions

Is there a proof showing the bias (or lack thereof) of the sample Pearson's correlation for discrete interval variables? In particular, I am interested in how such a proof handles the expected value ...
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22 views

Sample correlation matrix of discrete variables

Consider a population where each member is represented as a set of N correlated trinary variables (each coded as $\{-1, 0, 1\}$). I am trying to get an estimate of the mean of all elements in the ...
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1answer
62 views

Discretizing Continuous Outcomes: good examples?

My continuous dependent variable has a lot of error in it. Hence, I was thinking of discretizing it, to reduce the error for my modeling effort. But firstly, the main focus of my modeling effort are ...
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1answer
15 views

Combine Multiple Discrete Probability Density Functions

I'm a bit stuck trying to figure out the combined probability from several discrete PDF's. Lets say I have a bunch of different classes (Truck, Sports Car, Station Wagon, etc) and a bunch of ...
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1answer
78 views

distance measure of two discrete probability histograms (distance between two vectors)

I have multiple sets of discrete probability histograms(vectors) and I want to measure the distance between each histogram. I have done some research but I am in doubt. Literature suggest I could ...
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26 views

How would you correlate time series (price changes) to a discrete event happening?

I'm not sure what kind of model you would use here... But say you are looking at the price of the S&P 500. Suppose... If the market trends up, then everyone is happy and more likely to spend. ...
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55 views

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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19 views

Something like PCA for nonlinear discrete data?

I have a multi-dimensional discrete dataset. I know that the relationship between the components is nonlinear, but I don't know anything else. Preliminary inspection of some components of the data ...
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15 views

PCA for mixed variables

I have a dataset which contains many variables : continuous and discrete variables. I have a discrete variable adress which can include many value (if for example the customer changes his location, ..)...
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1answer
47 views

Discrete or continuous variable

I am trying to model Ip adress to cretae a fraud detection framework. So I am wondering if Ip Adress is a continuous or discrete or categorical variable. Bests
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20 views

Does it make to sense to derive a new column based on quantiles?

I am working with a dataset with alcohol levels. It looks something like this: Alcohol Level 10.34 3.21 323.12 ... I'm wondering whether it is common to "bin" ...
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1answer
12 views

computing P(a∧b) given P(a) and P(b) empirical distributions over 2D space

I know this is really basic but I have been unable to find anything to confirm or refute my understanding. Suppose two discrete, independent, empirical random variables $A$ and $B$ which are ...
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0answers
20 views

Transformation and standardization for discrete features?

I have a dataset consisting of continuous and discrete features (predictors). For the discrete features, I have integer values (e.g. 0, 5, 20, 30 etc.). Of course, for the continuous features I could ...
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1answer
34 views

How to report a value determined from a cumulative sum?

I'm reporting on methods that use discrete distribution data, for example: ...
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0answers
47 views

Descriptive formula for the mean of a discrete frequency distribution

I'm trying to typeset a formula for an R expression that determines the mean value from discrete distribution data. Here's some example data to describe my question. ...
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0answers
43 views

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. ...
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16 views

R visualization for discrete variables [duplicate]

What are the good data visualization tools/packages in R to visualize relationship between two discrete variables? Simple box-plot is not sufficient and can be misleading. Any other approach?
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2answers
81 views

Calculate probability distribution table for dates

I'm a software developer. Over 10 weeks our team has had the following estimations/actuals for how much work we can complete in points: ...
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12 views

Can optimising thresholds for discretisation lead to overfitting in Bayesian networks?

In Bayesian networks continuous data is often made discrete, for example: < 21.5 becomes 0 21.5 > .. < 43 becomes 1 > 43 becomes 2 If you run an ...
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21 views

Discretization for a bayes network model with small sample

I have been playing around with a Bayesian network toolbox for prediction and classification. I have had good success with the examples but I'm now stuck on how I should proceed with my scenario. I ...
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1answer
57 views

Exploring the relationships between discrete and categorical data

When you want to test the relationship (correlation) between two continuous variables, the main methods are easily learnt and very well documented. Scatterplots with regression lines, pearsons ...
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2answers
77 views

Methods for modeling discrete dependent variables and categorical independent variables

I need to determine if there are relationships between discrete dependent variables and categorical independent variables. To give some examples, one discrete dependent variable would be salary and ...
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21 views

How to compute a mean of some numbers from normal distribution? (using continuity correction) [closed]

In practice, specifically writing a paper, we often need to compute an expected value of some sample drawn from a certain continuous distribution. Let's say, draw 100 numbers from $N(0,1)$, and $f(x)$...
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1answer
59 views

MLE for discrete uniform distribution [closed]

I am trying to find $N$ by MLE for several discrete uniform distributions involving a parmeter $N\in \mathbb{Z}$. If the interval $X$ is defined on is $X\in (N,N+1,...,N+10)$ then I think $\hat{N}=\...
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2answers
147 views

Probability distribution of rare condition count

A population of t=310M experiences an environmental change that causes one in s=112M of them to acquire a particular condition c, each one independent of the others. What is the probability p that ...
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3answers
265 views

Visualize bivariate binomial distribution

Question: what does a bivariate binomial distribution look like in 3-dimensional space? Below is the specific function that I would like to visualize for various values of the parameters; namely, $n$,...
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3answers
206 views

Comparing two (or more) discrete distributions

I would like to know what the most powerful way of comparing two (or more) discrete distributions is. I know that the Kolmogorov-Smirnov test could be used (if corrected for the discrete ecdfs), and/...
2
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0answers
88 views

Combining Bhattacharya Distance (or A Measure of Similarity) — across Different Variables (Properties)

We have a series of observations of different properties (such as heart rate or blood sugar level and others as well) across different days from different people from different geographical regions. ...
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1answer
109 views

chi-squared with too many degrees of freedom

I have a third party random number generator with a period approximately greater than $63*(2^{63} - 1)$ which generates numbers in the range $[0,2^{32}-1]$, ie $2^{32}$ different numbers. I've made ...
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1answer
42 views

Is it better to use the original continuous or discretized data in building a model?

I am currently competing in a Kaggle competition and wondering is it a good choice to discretize particular variables. I saw that some specific continuous variables have almost all values that are ...
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1answer
47 views

Throwing two four-sided dice; min/max problems

Suppose two four-sided fair dice. Let $X = min(X_{1}, X_{2})$ and $Y = max(X_{1}, X_{2})$ where $X_{1}$ is the result of the first dice and $X_{2}$ the result of the second dice. What is the PMF of ...