A vast area which includes generating results from computer models.

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Simulating from normal copula in R with varying correlation matrices [migrated]

I'm trying to simulate correlated normal copula realizations using the copula package in R. I have estimated the varying correlation matrices and stored them in an ...
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26 views

Correlation analysis with simulation

I need to determine if two variables are correlated (have a relationship between each other). Issue 1: both variables take on values greater than O, in which, I can not assume normally distributed. ...
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1answer
18 views

Check validity of a time series regression model using simulated time series dataset

I want to generate two artificial time series, one of which acts as the explanatory variable and the other as the dependent variable for a regression model. Can anybody suggest as to how to proceed ...
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8 views

Scaling parameters to lie in unit hypercube — how to understand this notation?

I am attempting to emulate a simulation in a paper I am reading. The model includes two parameters $\theta_1,\theta_2$. These parameters are scaled to lie in the unit hypercube. That is, where the ...
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13 views

Studying how parameters affect standard deviation of skewed data

I'm running a bunch of simulations that are modeling the first time a neuron fires when it receives stochastic input and has intrinsic noise. The program I wrote creates a dataset of a bunch of time ...
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5 views

Error term used in model simulation to analyze it accuracy [closed]

What is the common error term used in simulation for mathematical model to test it accuracy?
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53 views

How to Validate a Monte Carlo Simulation

I have historical data of a production process, and I've being asked to build a simulation model to predict its performance in the future. Using the historical data, I've being able to obtain the ...
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1answer
15 views

Simulating a Stochastic Integral of OU process

The stochastic integral I want to simulate is $$\int_{0}^{1}J_c(s)dJ_c(s)$$ where $J_c(s) = \int_{0}^{s}e^{-c(s-r)}dB(r)$, is an OU process. I simulate the data using Matlab and the sample codes are ...
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17 views

Definition of Simulating Data [closed]

What is the best definition of simulation of data (with author name ) and some information about simulation .
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9 views

Best way to tackle heterogeneity in oncologic models

I need to model the health outcomes from an immuno oncologic treatment to which patients are responding differently depending on their immune condition, which is unknown to the investigator. I was ...
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0answers
13 views

simulation and model comparison

I created a simulation to compare a number of regression type models/estimators, lets call them M1, ...,Mn. for each iteration of the simulation run: I generate randomly data set X I generare ...
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1answer
50 views

Gibbs sampling, what to use?

My question concerns Gibbs sampling. Suppose that I have three unknown quantities, $\mu, \sigma^2$ and $c$. I have given prior information and I have given the likelihood which allows me to compute ...
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15 views

Comparing neuron “jitter” values across trials

I'm asking this question on the statistics forum because I'm wondering a bit about drawing appropriate conclusions supported by statistics from skewed data (if it belongs on another area of stack ...
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37 views

Is it possible to use runif() to generate a vector of random variables with different probabilities? [duplicate]

Here's the question I have to solve: Let X be a random variable with pmf as given: P(X = 1) = 0,1 P(X = 2) = 0,3 P(X = 3) = 0,6. Simulate this distribution ...
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4 views

Simulation Model Performance for Flood Quantile Estimation at Ungauged Site

I have proposed a model that is the modified ANN to estimate flood at ungauged site. In order to test the performance of the model, i want to design the simulation for ungauged estimation problem. Did ...
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20 views

hypothesis test observed to simulated, z-score or not?

Lets say we have data set with an x and a y variable. We have an effect size from a linear model called of ...
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1answer
25 views

Cauchy Distribution used in error term in simulation [closed]

What is the reason used Cauchy distribution in error term for simulation of data. I see a lot of researcher used the distribution but does not stated the reason why used Cauchy Distribution.
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25 views

multivariate chi-square distribution R/Simulation

Is there some R package that calculate the quantiles\percentage of some vector of multivariate chi-square distribution? If there isn't can I simulate these percentage somehow? Thanks a lot.
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1answer
17 views

simulate sub group data for logistic regression

I want to simulate a data set for logistic regression in which my $Y_i \sim Bin(n_i, p_i)$ and $n_i >1 ~ \forall i$. I want something like: In another question, data has been generated for a ...
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40 views

Multiple imputation simulation problems, bad imputations or bad simulation?

I'm relatively new to simulations, R, and multiple imputation. I am writing a simulation to better learn multiple imputation on my own. Here is my simulation of MCAR: ...
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29 views

2 Dimensional Random Walk Simulation

I am trying to simulate random diffusion of particles using a random walk diffusion model. I have used probabilities of movement of particles in a 2D area, to be 1/4 in all 4 directions. The confusion ...
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1answer
53 views

Intraclass correlation coefficient in Bayesian statistics

I need some references about intraclass correlation coefficient in Bayesian statistics and hypothesis testing. I already take a look in A. Gelman, J.B. Carlin, H.S. Stern and D.B. Rubin, Bayesian ...
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0answers
15 views

Which methods do people use to understand queueing networks?

Queueing networks can be analyzed through analytic results (in some cases), approximation methods or simulation (discrete-event simulation, system dynamics). Analytic solutions do not exist in general....
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22 views

Using ABC package from R cran with a C++ simulator [closed]

I developed a simulator in c++ and I would like to use the R Cran package "ABC" from Csillery et al with that simulator. There seem to be many ways to make the two programs interact, but what would ...
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8 views

Simulating qualitative interaction in survival analysis

I am trying to simulate the survival data that can fit the model: $$h(x) = ho(x) exp (a_0*Treatment + a_1*Treatment*x_1 + a_2*Treatment*x_2)$$ Whereas treatment is an binary variable (0 = control ...
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2answers
68 views

Rule of Succession for Unfair Coin

Given the first n flip results from an unfair coin, we wish to estimate the probability that the next flip is a heads. I can take 2 approaches to this: Frequentist:...
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1answer
47 views

Find 'p' in geometric distribution when 'P(X)' and 'k' are known

This may be a bit more of an advanced algebra question, but here goes: I'm trying to use the equation for a geometric distribution P(X) = p(1-p)^k to find the ...
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7 views

Simulating interaction term in Cox model

I am trying to simulate the survival data (by using Weibull distribution) that can fit the Cox model below: h(t) = ho(t). exp(beta1 * X1 + beta2 * X1 * X2) X1 and X2 are binary. I haved tried using ...
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7 views

Fully identified moment matching with simulated method of moments

I am struggling with some results regarding the model fit in this paper (p. 49). The authors set up a simulated method of moment estimator, using 8 different moments to match and 8 different ...
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0answers
34 views

Monte Carlo vs simulation in GARCH (package “rugarch” in R)

What is the difference between a GARCH simulation and a GARCH Monte Carlo simulation? I look in the vingette for the "rugarch" package in R, Introduction to Rugarch. In section 6 Simulation on page ...
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34 views

How to generate new random variables after using PCA for dimension reduction?

I want to be able to generate random variables, that (more or less) match the distribution of some observed data set. The data set is high dimension and I have reduced the dimension using PCA. Only ...
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29 views

Indirect solution for maximum entropy through sampling?

Is there a way to sample from a finite set $\{A,B,C,D\}$ such that the limiting empirical proportions converges to the maximum entropy solution of their probabilities consistent with known constraints?...
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2answers
34 views

Simulate 1000 samples from a bivariate normal distribution

I know the code to generate two correlated variables (r=0.5), for example with 100 numbers each: xy<-mvrnorm(100, mu=c(50,60), matrix(c(1,0.5,0.5,1),2)) But how can I simulate 1000 samples ...
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17 views

Multilevel Power of a Mixed Model

For my dissertation I have data from 57 employees that responded the same survey on 11 occasions (i.e., 11 observations per person for each variable). All variables I am interested in (and are ...
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15 views

How to aggregate many simulation runs for curve-fitting?

I have results from about 200 runs of a simulation model. The results contain a stochastic response variable which I want to approximate with a curve-fitting approach. So far, I have opted for ...
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31 views

alternative to the delta method for computing the variance & CI of products of probabilities

I'm trying to find a way to calculate the confidence interval of the product of probabilities without using the delta method or Program MARK. I am using a logistic-exposure model to estimate the ...
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3answers
406 views

Simulate a Bernoulli variable with probability ${a\over b}$ using a biased coin

Can someone tell me how to simulate $\mathrm{Bernoulli}\left({a\over b}\right)$, where $a,b\in \mathbb{N}$, using a coin toss (as many times as you require) with $P(H)=p$ ? I was thinking of using ...
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0answers
5 views

Evaluate (user-defined) variance estimators in simulation environment?

I'd like to examine how a variance estimator that I constructed for complex surveys behaves in simulation environments, in a manner similar (and perhaps much simpler) to what Li and Levy (2009) at the ...
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1answer
33 views

Estimating normalization constant with Monte Carlo integration

Be $f(x)$ a function. Suppose that $f(x)$ integrates to a finite value $k$: $$\int_{-\infty}^{\infty}f(x)dx=k$$ The normalization constant of $f(x)$ is $1/k$. Monte Carlo integration can give an ...
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1answer
19 views

Why use Coded Variables in Experimental Design?

Full-disclosure, I'm not sure if this ENTIRELY on-topic. Often times, most texts will suggest that we code our variables. i.e. If we move from 345 to 350 to 355, we code our variables as -1, 0, and 1....
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20 views

regarding generating synthetic data simulating the real data

We are trying to develop some predictive models. The current scenario is that we have to rely on synthetic data at first since the real data set will not be available quite soon. It is understandable ...
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18 views

Efficiently sampling from Markov Chain with low-probability transitions

I need to sample a large number of paths from a Markov Chain with known state transition matrix $T$, where some of the state transitions are low probability (~0.01%). For example, I might have a large ...
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0answers
35 views

Endogeneity for logistic regression

I would like to construct a setup where there is endogeneity between a binary independent variable and (in the latent formulation) the logistic noise. The set up has to be easy to simulate and ...
4
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1answer
44 views

Question about accuracy in Monte Carlo integration

Suppose that we want to estimate the integral: $$\psi=\int_{a}^{b}h(x)dx.$$ Let $\hat{\psi}$ be the Monte Carlo estimator. As far as I know, if we desire an accuracy up to the fourth decimal, we need ...
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0answers
31 views

Obtain marginal CDF from joint CDF by simulation

How can I evaluate the marginal cumulative distribution function of a set of random variables for which I do not have the CDF in closed form. I can, however, simulate from a joint distribution ...
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2answers
269 views

fat-finger distribution

Brief question: Is there a fat-finger distribution? I'm sure that if it exists, then it has a different name. I don't know how to formulate it as an analytic function. Can you help me either find ...
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1answer
73 views

monte carlo simulation using exponential distributions

I'm trying to simulate a stochastic model of deterministic exponential population growth, where $dN/dt = rN$ where $N$ is population size and $r$ is rate ($t$ time). I'm assuming there's no carrying ...
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29 views

Why don't I get intervals which don't contain parameter by simulation?

I effect 100 simulations, and with a confidence level 95% I expected to get by simulation 5 coinfidence intervals approximately that not contain the paramater. I always get 100 confidence intervals ...
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79 views

Bootstrapping in Binary Response Data with Few Clusters and Within-Cluster Correlation

Beware: This is (almost) a cross-post to a thread I started on the Statalist but that has not received much attention so far. Introduction I am learning about the problems when conducting ...