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0answers
8 views

AutoUniv implementation in Linux? [on hold]

AutoUniv is a data generator with an available implementation for Windows. Is anybody aware of implementation in unix?
3
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2answers
34 views

generate synthetic data from a sample data

If I have a sample data set of 5000 points with many features and I have to generate a dataset with say 1 million data points using the sample data. It is like oversampling the sample data to generate ...
0
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0answers
42 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 ...
0
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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
30 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 ...
0
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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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1answer
167 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 ...
3
votes
2answers
120 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 ...
5
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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 ...
6
votes
1answer
139 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. ...
0
votes
1answer
436 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) ...
2
votes
0answers
303 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 $$d_{1,t}=\mu+\...
5
votes
2answers
755 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 ...
1
vote
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 ...
0
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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 ...
1
vote
2answers
144 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 ...