Questions tagged [continuous-data]

A random variable $X$ is called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A random variable is continuous if and only if its cumulative probability distribution function is a continuous function.

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Feature selection using chi squared for continuous features

I'm looking at univariate feature selection. A method that is often described, is to look at the p-values for a $\chi^2$-test. However, I'm confused as to how this works for continuous variables. 1. ...
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Identifying non-linearities in relationship between variables

Logistic regression is often used to identify the effect of $x$ on a binary variable $y$ after adjusting for potential confounders $x_1,...,x_n$. In the medical literature, I will sometimes encounter ...
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Truncated Explanatory Variable

I am running a model where one of the explanatory variables is truncated. In particular, the variable measures the duration of unemployment (retrospectively) in months and it is truncated at 2 years, ...
244 views

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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Autoencoder with Mixed Data

Is it reasonable? The categorical features can be binary ("true" or "false") or strings, which are one-hot encoded. Some continuous features may be integers, which are treated as real values. If an ...
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How to estimate a continuous analog of the (discrete) vector autoregression (VAR) model

I have some ten to 100 thousand observations on each of around 500 entities. I have good reason to believe that these observations all mutually influence one another, in possibly complicated ways, or ...
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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 ...
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What are best practices for visualizing/selecting visualizations for continuous data?

There appear to be a large number of rules of thumb for histogram bin size and kernel selection for density plots. Are histograms and/or density plots really the best visualization for a single ...
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Splitting a variable with nominal and numeric values

I have a variable that has both numeric and nominal components. The source has a documentation which helps in identifying which is which and for splitting into their proper components. I will do ...
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Testing if treating a categorical variable as continuous is okay

Pardon me if this is a simple question, but I haven't found a great resource for this just yet. Yes, I know that when possible, we should try to treat ordinal variables as categorical rather than ...
277 views

Dependent variable maximum value contingent on independent variable

I am trying to create a model for debt collections. In the past I have used logistic regression to predict pay/no-pay. This has worked well but has a few unfortunate consequences. People are more ...
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How to analyse a continuous response having a bimodal distribution?

I am investigating unconscious racial prejudice as a predictor for guilty or not guilty judgements (Using SPSS). I have a continuous variable for unconscious racial prejudice (higher numbers equal ...
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Is continuous mutual information the correct analogue of the discrete version?

I'm interested in the mutual information of two continuous random variables $X$ and $Y$. Shannon defined differential entropy as $h(X) = -\int p_X(x)\log p_X(x) dx$, where $p_X$ is the probability ...
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What is the most appropriate way to compare means when group size is markedly different?

This scenario seems to be arising more and more with the usage of large datasets in an attempt to identify pilot data for associations, etc. I'm trying to figure out what method - if any - is the most ...
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Correlation analysis on two different groups of continuous heterogeneous variables with different range/scales in R

I would like to perform in R a initial simple correlation analysis, between a gene signature that i have identified, and some continuous clinical parameters, measured on the same patients, to identify ...
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Family distribution for continuous count data

I need to model the variable Total motile Count which describe how many million sperm cells in an entire ejaculate are motile. It is not a proper count since it is calculated as a product of other ...
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Regression modelling with mixed data set: categorical and numerical predictor variables

There are thirteen predictor variables which are a combination of 8 continuous, 4 binary and 1 categorical variables. The dependent variable is again categorical. I understand that I need to use dummy ...
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Marginalizing multivariate-normal distribution canonical form

Regarding the problem of margenalization of canonical forms of multivariate gaussian distribution it was mentioned in probabilistic graphical models text book that $$\int{C(X,Y;k,h,g)}dY$$ is ...
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Unified Variable Classification

I am trying to go beyond Stevens' Level of Measurement Typology. Here is what I have so far: Discrete Variables Nominal (like Apple, Banana) Ordinal (like 1, 2, 3) Count (like 0, 1, 2) Incremental (...
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Why big difference between categorical and continous variable inregression analysis?

I am currently doing a survival analysis where I want to adjust for several confounders. One of my variables, which I will name MyScore is a score from 1-5. When I enter MyScore as a continuous ...