Questions tagged [simulation]
A vast area which includes generating results from computer models.
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Official name of a common type of Bayesian simulation study
There is a kind of simulation study that is commonly used to validate an implementation of a Bayesian model:
For independent replication $i = 1, ..., n$:
Draw a set of "true" parameters ...
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In sports modelling, are hot simulations better or cold simulations?
I'm thinking here largely of the context in which someone has an Elo rating model for a particular sport.
To calculate things such as how often the team makes the Finals series, or wins the ...
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How closely related are the Gelman-Rubin statistic and the autocorrelation length?
When monitoring the convergence of parallel MCMC chains, some people measure the autocorrelation length, others the Gelman-Rubin statistic. (There are others who use some other statistic and still ...
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Copulas for generating uniform random variables with correlations
I want to generate uniform random variables which have a correlation structure defined by a graph i.e. a variable is only correlated with its neighbors in the graph and is uncorrelated with the rest ...
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Simulate Gaussian variables conditional on their sum of squares
Consider a $d$-dimensional Gaussian random vector $\mathbf{Z}=[Z_i]_i$
with mean $\boldsymbol{\mu}$ and covariance matrix
$\boldsymbol{\Sigma}$. What would be the more efficient method(s) to
simulate $...
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Skew of p-value distribution under composite null hypotheses
On this page it says
...if HA holds, the p-values have a distribution for which values near 0 are more likely than values near 1. However the p-values may have a distribution that is not ...
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Generating random matrices with specific equality constraints
Suppose I want to generate a nonnegative $n \times n$ matrix $\mathbf A$ for an odd $n$ (say, $n=5$ for a good enough example), such that
the individual elements are drawn from a uniform distribution
...
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Generate Posterior predictive distribution at every step in the MCMC chain for a hierarchical regression model
I'm trying to fit a Bayesian Hierarchical regression model with a random correlated coefficients using R ,I'm using data having 160 groups (schools) to fit a model of math score as a function of one ...
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Probabilities arising from permutations
Certain interesting probability functions can arise from permutations. For example, permutations that are sorted or permutations that form a cycle.
Inspired by the so-called von Neumann schema given ...
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Simulate correlate random variables with given marginal distribution where one is always larger
Is it possible to simulate pairs of random variables with a given marginal distribution and population correlation where one random variable is larger than the other?
More formally, I need to simulate ...
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Justification of acceptance probability in simulated annealing
In simulated annealing the acceptance probability for a new state in step $k$ is traditionally defined as
$$ P(\text{accept new})= \begin{cases}
\exp(-\frac{\Delta}{T_k}), & \text{ if } \Delta \...
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How to simulate data with values of Mardia's Kurtosis?
I have two (related) questions regarding the simulation of correlated, non-normal data with a user-specified value of Mardia’s 1970 multivariate kurtosis.
(1) It is very common in my field to use the ...
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Power calculations for Wilcoxon test
I am running a Wilcoxon test to compare means between two groups (control and experiment) of unequal sample sizes. The distribution is right skewed and bound by zero for both groups.
I would like to ...
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Interpolation and Sample size when Visualizing distributions
Let's assume a stochastic simulation or test with a control variable. The task is to visualize the distribution to demonstrate the effect that is being researched. The objective is to get smooth plot, ...
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How do I simulate a random valid correlation matrix of ordinal variables given a list of marginal probabilities?
I am trying to use R to simulate random variations in a real dataset with a known number of categorical and continuous predictor variables, as well as known marginal probabilities for each ordinal/...
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