Questions tagged [simulation]
A vast area which includes generating results from computer models.
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Simulate Gaussian copula with negative pair-wise correlations
I am now trying to simulate a multidimensional (let's say 4 dimensions) Gaussian copula. Given software restrictions, I can only use Excel for this simulation. That is why I am trying to implement the ...
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Steps for Forecasting with known copula's parameters
I want to calculate the Mean absolute percentage error (MAPE) for my copula model. I am stuck at the forecasting step. I am not specifying the copula here for different data pairs.
I have two time ...
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Is "relative risk time" meaningful? (transient relative risk)
Context:
I'm trying to specify a data-generating / mechanistic model for a simulation study. I assume that exposure $e$ (a short event) has a transient effect on the relative rate of another process $...
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Simulate $p$-value of $\chi^2$-test
The R function chisq.test has an simulate.p.value argument that uses permutation for resampling. I know how to implement this ...
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Can I use simulated data only for testing a Random Forest regression already trained on real data?
I am working, using Python, on a Random Forest Regression for the prediction of a target variable. I have trained it and tested it on real data, obtaining satisfying results. Now, I would like to ...
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Difference in means and variances of dependent samples
I am performing a simulation study where different values of an exposure X are repeatedly assigned to the same individual (200x in a sample of >10000 people). The way that assignment is done is ...
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Recycling MCMC samples for another data set from the same distribution
Suppose I'm given $\theta_0$ and I want to sample data from a density $f(Y|\theta_0)$ and then sample from the posterior of $\theta|Y$ (given, obviously, some prior). I want to do this lots of times, ...
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How to simulate this AR(1): Xt =2+0.8(Xt_1 −2)+εt series in R? [duplicate]
I want to simulate an AR(1) model defined as follows:
$$X_t = 2 + 0.8(X_{t-1} −2) + \varepsilon t$$
but I do not know how to interpret the constant $2$ in this term.
How do I simulate this in R?
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Is this a reasonable way to check the quality of simulated data in MCMC inference?
I have a hierarchical Bayesian model that looks like this:
$\alpha_i \sim \mathcal{N}\left(\mu_\alpha, \sigma_\alpha\right) \tag{1}$
$\beta_i \sim \mathcal{N}\left(\mu_\beta, \sigma_\beta\right) \tag{...
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Expected Value Chi Square distribution
I'm trying to simulate the distribution from the sample variance $s^2$ and compare it with the theoretical distribution.
Therefore, I perform a fairly simple simulation (upfront, I'm not a ...
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Least-bad stepwise procedure for a simulation that shows issues with stepwise regression
I am well-aware of the issues that stepwise regression causes. I want to demonstrate some of them via simulation in a particular situation.
I am thinking of a regression where I have some categorical ...
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How to deal with competition for variance between a fixed and random effect?
I am performing an analysis on data in which there is a hypothesized relationship between X (predictor) and Y (the response) across a broad area, but random (no relationship) within groups of ...
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Power calculation with a binary outcome (using a R package & manual simulation)
I am trying to compare three different methods for power calculation under the same setting. Although I understand that the power estimates from each method cannot be exactly identical due to ...
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How to Simulate Data for a SEM Model with Moderation Effect Using R?
I'm working on a project where I need to simulate data for a Structural Equation Model (SEM) that includes a moderation effect. Specifically, I have three latent variables: an independent variable (IV)...
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How to simulate a time-series based on other time-series that have different seasonality (and other effects)?
I have a list of solar production data time-series for a set of houses in a given area, and I need to simulate the solar production vs time curve of a new house in the area. The sum of the total ...
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Sample size for a vector of proportions and simulation
Currently, there are more than 10 variants of omicron virus.
Say, variant proportions are X1=0.1, X2=0.35, X3=0.15, etc. I need to calculate the number of samples needed to detect the proportion of ...
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How to guess a random walk to achieve max sample correlation?
Define this 1-D discrete random walk start from 0: roll a die (the die may or may not be fair, the fixed probability of each face is unknown to the observer/guessor)...
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Data modelling as a surface
I want to model waste generation in a city using data from the containers. I have the location and fill levels of each container over time. My idea is to use the average amount of waste in each ...
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Are the p-values obtained on the same sample using synthetic AA tests (Monte Carlo) independent values?
Let's say we have the following procedure.
We take a fixed sample of size n and perform the procedure 1000 time:
we divide (split) it equally into 2 groups;
we calculate p value using the F function (...
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Didactic example of mean-variance dependency in linear models
I'd like to illustrate the importance of accounting for the dependency between mean and variance in inference with linear models. Is my example below a good one? Do you agree with my comments on it?
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Simulation of Random Processes to Check Stationarity
I am wondering if this is a valid approach:
I want to validate that certain random processes are not weakly stationary (constant mean, covariance depends on the lag, finite variance) through ...
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I want to show by simulation that the Wilcoxon test is more robust than the Student test for non-normally distributed data
I want to test by simulation that the Wilcoxon test is more robust than the Student test for non-normally distributed data.
For example, I'm testing the ...
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Mixed model: Which parameters to provide for sample size calculations?
I am currently planning an analysis in a relatively new area of research and would like to provide data that will allow for future power analyses. Unfortunately, I am completely lost in the ...
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What is the standard deviation/uncertainty of a single observation in a meta-analysis?
I am running a simulation with parameters based on an existing random-effects meta-analysis. I would like to draw individual patients in the treatment group from a normal distribution with µ=the ...
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When can I use bootstrapping in a microsimulation model?
I'm investigating uncertainty in a linked series of microsimulation models, the outputs of each feeding into the next.
The first model (model A) generates individuals by resampling them - using a ...
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Calculating Sample Size for Cumulative Link Mixed Model (CLMM)
I am going to collect data in which each participant answers to 3 questions to 18 vignettes (each vignette has 3 questions), each question with likert scales 1-5. The dependent variables (questions) ...
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Beta-binomial relationship between dispersion and correlation parameters
Context: I have created a beta-binomial model using glmmTMB() from the glmmTMB package and I am now trying to simulate a beta-...
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How to simulate non-standardized artificial data for logistic regression?
I would like to simulate data for a logistic regression with the predictor variables on their original scale.
There are, of course, a litany of similar previous questions (e.g., here, here, and here). ...
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How can I simulate the path between two defined points but also define the overall step variance?
As stated in the question. I’m wondering if it’s possible to simulate a random walk between two fixed points (always start at A and finish at B) where the variance of the difference of steps is also ...
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Forecasting positive time series with missing values and few observations
I am working on forecasting a positive time series dataset of prices with missing values and only a limited number of observations. Specifically, I have 150 observations, one per week, and I need to ...
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ABC (Approximate Bayesian Computation) Sampling, Simulating data from Complex models
In ABC sampling methods, Rejection, MCMC and SMC, when we sample potential parameter values from the prior/proposal, we then use those parameters on our model and simulate data values. This can be ...
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Extended Hidden Markov Models (HMM) parameter estimation
For simpler HMMs, we can use algorithms like Viterbi training (not decoding) or Baum Welch to estimate the parameters that best describe the observed data.
How do we do the same when using a more ...
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Help in simulation for bivariate residual entropy
I am reading a research paper research paper. Let $X=(X_1,X_2)$ be a bivariate random vector with survival function $\bar{F}(x_1,x_2)$.
The the condition residual entropy for the condition ...
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How to evaluate an Earth system model in light of the spatial variability of observed variables?
Context
My effort is to evaluate the performance of a physics-based numerical model to determine how well it simulates different state variables of a soil column (1D inside the model). The temporal ...
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How to compute relative error of multi-dimensional time-series?
I have written a python script that uses a variety of different integrators to simulate the gravitational N-body problem. I would like to compare the positions obtained from my simulation to the ...
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How to Calculate Number of Repeated Tests to Achieve a Target ICC?
I am designing a case study and will be measuring something at baseline, periodically over time, and at post-testing. I will use the baseline measures to be able to calculate the 'minimum detectable ...
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Simulate bivariate bernoulli responses with predefined beta coefficients
I have a specific data matrix with features (mainly categorical). I want to simulate a multivariate bernoulli response, for example bivariate, but with a predefined vector of beta coefficients (most ...
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Should I use a one-sided or a two-sided confidence interval?
Context:
I am teaching a subject and I prepared a multiple-choice quiz for my students.
To have a feeling for which is an acceptable grade I decided to compute a baseline score, which is the score ...
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How can I determine if a system is equilibrated?
Cross-posted in SCSE and MMSE
I am experimenting with a new MCMC protocol and new research.
In the context of Monte Carlo simulation, a "state of equilibrium" refers to a condition where the ...
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Stationary Bootstrap Block Size Impact on Portfolio Simulation Results
I'm analyzing simulated portfolios generated using the stationary bootstrap method proposed by Politis et al. (1994). This method is expected to be robust to the choice of average block size, as it ...
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Post hoc power for multiple logistic regression
I have data frame named "finalend", I conducted multiple logistic regression model named "model" with all predictors as categorical or binomial variables and "TestAnxiety"...
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Assigning variance-covariance matrix in generating artificial data for mixed-effect model
I can’t understand specifying correlation between within-participant conditions when generating artificial data for mixed-effect model regression. It would be grateful if you could help me.
My story ...
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When do we not know the distribution of residuals?
In a previous question (How does simulation help validate model assumptions?), I received the following comment:
"When a model is too complex such that a derivation of the distribution of the ...
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How to estimate required sample size for the two-sample Kolmogorov-Smirnov test
I have a simulation model which produces a value for an output variable. Running it many times gives skewed distributions for this output variable. What I'd like to do is compare two distributions, ...
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Specifying random effects for simulation of categorical data
I am simulating data for an experimental design with two conditions. I specified the following multilevel model:
$$
y_{ijk} = \beta_0 + u_{0j} + v_{0k} + (\beta_1 + u_{1j} + v_{1k}) * X_1 + e_{ijk}
$$
...
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How to show in R, using a simulation, that when sampling from a normal distribution, the sample mean and sample variance are independent
What is the best way to show that when sampling from a normal distribution, the sample mean and sample variance are independent?
I know the theory behind this result, I would like to show it using a ...
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Simulate a distribution from a fitted beta-regression model for a density plot in R [duplicate]
I have produced the following figure by simulating some values from a fitted gamma regression with a low AIC value that provides the closest approximation of my raw data out of all of my models, and ...
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Sample size in simulation and stopping criteria
I want to estimate the average of a random variable by simulation. Also, I want to estimate a proportion by simulation.
I know that there are formulas to calculate the minimum sample size so that the ...
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Inference for Binomial proportion with estimated p but unknown N
Let's say I own a bakery that, among other desserts, sells one really tasty chocolate cake. It's so good that I've estimated that I've estimated 80% of my daily customers will buy a piece of cake, ...
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Simulating non-zero mean autoregressive (AR(2)) samples
I asked this question in stackoverflow, with no success. I am hoping that i might get some suggestions here.
I am trying to generate non-zero mean AR(2) samples using statsmodels package. But it seems ...
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