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32 views

Realistic Test Data Generation

I search for some literature or references, or also only some tips for the topic of test data generation that is realistic and what it means to the data to be realistic. Example Questions that are ...
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2answers
56 views

How can I generate data for a GLM that explains my outcome well?

I want to test several glm methods of an outcome that follows a gamma distribution. I can generate this outcome like this: y <- rgamma(100, shape=0.5, rate=1) ...
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0answers
28 views

Test hypothesis of rare event with real life data using a Bayesian Model

Since I found out what Bayesian Theory I got really interested in using it in my everyday life to find a numerous of things, but I wasn't able to get any result due to my lack of understanding of ...
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0answers
12 views

Improve a tagging system based on future data learning

I need to improve a system that tags events as good/bad for model training set creation. The current system relies on 1-2 data points following the event (for the same customer) that could happen ...
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0answers
15 views

General question about generating data, using GEE and testing the results

I am new to GEE and try to understand it by using it. Now I have troubles to understand how the "gee" package in R works. I start by explaining what I intended to generate and what my questions are. ...
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1answer
155 views

Generating data from Probit regression, cut off 0 and variance 1 necessary?

I am trying to create a dataset using a Probit regression model in R, where I have an intercept and three covariates. I first fix a set of coefficients for the three covariates, generate these ...
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2answers
116 views

Generate fake data consistent with adjusted R^2 pattern

Is it possible to specify a vector of adjusted $R^2$ values (or any other measure like AIC, BIC, $C_p$) for the set of all possible models in a data set, and then generate data that is consistent with ...
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1answer
1k views

How to generate survival data with time dependent covariates using R

I want to generate survival time from a Cox proportional hazards model that contains time dependent covariate. The model is $h(t|X_i) =h_0(t) \exp(\gamma X_i + \alpha m_{i}(t))$ where $X_i$ is ...
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1answer
132 views

creating multiple categorical variable with specified degree of association (correlation) matrix

Lets say I want to generate data with particular association matrix. I am taking phi coefficient` as measure degree of association. Here are examples using R. ...
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1answer
383 views

with Excel, generate 0 with n% probability OR generate 1 with (1-n)% probability

(first of all I simplified my question) depending on the input info below, I want to create proper excel function in output part. what I require verbally in output part under "status (0 or 1) ...
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0answers
293 views

Generate correlated AR process for given correlation between demand series

How can I generate two correlated $AR(1)$ data series with given correlation between $d_{1,t}$ and $d_{2,t}$, $r_{12}$, where $\rho_{12}$ is correlation between the two error series ...
5
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2answers
717 views

Random generation of n-dimensional data with possibly correlated variables

I would like to generate a set of artificial data using another input set from which correlations between variables can be extracted. Not all variables are binary, but the data can easily be extended ...
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1answer
1k views

How to generate correlated test data that has Bernoulli, categorical, and continuous vectors (in R)?

I'm looking to generate a set of 5 random variables and enforce a dependence structure between them and onto a dependent variable Y. I understand how to generate correlated random variables for ...
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0answers
67 views

Generative model that penalizes clumping of data

I'm interested in modeling a generative process that encourages data to be "evenly distributed" over its support, i.e. clumping of data points is penalized. For example, if I have a mixture ...
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2answers
142 views

What is the correct likelihood function for an sequential, adaptive data generation process?

Consider the following sequential, adaptive data generating process for $Y_1$, $Y_2$, $Y_3$. (By sequential I mean that we generate $Y_1$, $Y_2$, $Y_3$ in sequence and by adaptive I mean that $Y_3$ is ...