Questions tagged [monte-carlo]

Using (pseudo-)random numbers and the Law of Large Numbers to simulate the random behavior of a real system.

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397 views

expectation of log of expectation by Monte Carlo

When considering the approximation by Monte Carlo of an expectation of the form$$\mathfrak{I}=\mathbb{E}^X[\log\{\mathbb{E}^{Y|X}[h(X,Y)|X]\}]$$using a resolution of the form$$\hat{\mathfrak{I}}=\frac{...
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1answer
776 views

Simulating Monte Carlo with different standard deviations and interval confidence

I have a question regarding Monte Carlo simulation (direct simulation), applied to propagation of uncertainties. From what I understand Monte Carlo accepts random numbers of each input variable of ...
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712 views

Endogeneity in spatially lagged regression model

The standard convention in Spatial Statistic is that the spatial lag term in a regression model will be biased due to simultaneity. Looking at the following model, it would be difficult to argue with ...
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49 views

Keeping track of the variance of a Metropolis-Hastings estimator

Let $(E,\mathcal E,\lambda)$ and $(E',\mathcal E',\lambda')$ be measure spaces, $p,q$ be probability densities on $(E,\mathcal E,\lambda)$, and $\varphi:E'\to E$ be bijective and $(\mathcal E',\...
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How does the celebrated result about the diffusion limit of the Random Walk Metroplis-Hastings algorithm help us to find the optimal scaling

Let $d\in\mathbb N$ with $d>1$ $\ell>0$ $\sigma_d^2:=\frac{\ell^2}{d-1}$ $f\in C^2(\mathbb R)$ be positive with $$\int f(x)\:{\rm d}x=1$$ and $g:=\ln f$ $Q_d$ be a Markov kernel on $(\mathbb R^...
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53 views

Advantages of using t-value as test statistic in permutation tests?

I'm working with some permutation tests where my main aim is to evaluate a treatment effect, and I have a question about choice of test statistic. I've seen that some use β for the variable of ...
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44 views

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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99 views

Approximating the first moment of $h(x)$ where $x$ ~${\rm log\,normal}(\mu, \sigma)$

What is the best way to approximate $E(h(X))$, where $X$ ~ Lognomal($\mu, \sigma$)? So far, I can think of Monte Carlo Methods and Gaussian Hermite quadrature as below: \begin{align} E(h(X)) &= ...
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164 views

Computational entropy and Monte Carlo simulation

Is there a point at which the statistical properties of the random number generator will start to influence the results of Monte Carlo simulation? I have a scenario where I need to calculate the ...
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848 views

Population Monte Carlo Algorithm

I am trying to wrap my head around the Population Monte Carlo Algorithm. I want to implement it for a mixture model, but I am uncertain on how to proceed. I am mostly looking for references or ...
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177 views

Estimating parameters using Kullback-Leibler or Kolmogorov-Smirnoff via Nelder-Mead

I want to find the parameters of a model which specifies a set of classification probabilities, for say M classes. (I'll use the parameters in another model later.) Given a set of parameters $\theta$,...
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30 views

Bootstrapping for Control Variates

TLDR: I want to do Monte Carlo with control variates I work in the setting where you use Monte Carlo sampling to approximate the optimal coefficients for the control variates. I want to retain the ...
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44 views

Expected value of a “logistic uniform” multivariate

Let $\mathbf{a}_1,\ldots,\mathbf{a}_n \in \mathbb R^d$ and $b_1,\ldots,b_n \in \mathbb R$ be fixed. For $\mathbf{x} \sim \mathcal U([0,1]^d)$ and $j \in \{1,\ldots,n\}$, consider the real variable ...
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1k views

Expected value of softmax transformation of Gaussian random vector

Let $\mathbf w_1,\mathbf w_2,\ldots,\mathbf w_n \in \mathbb R^p$ and $\mathbf v \in \mathbb R^n$ be fixed vectors, and $\mathbf x \sim \mathcal N_p(\boldsymbol{\mu}, \mathbf{\Sigma})$ be an $p$-...
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99 views

Sampling from mixture of *unnormalized* densities

Suppose I have $n$ unnormalized densities $g_1(\textbf{x}), \ldots, g_n (\textbf{x})$, for $\textbf{x} \in \mathbb{R}^d$, and $n \gg 1$, which largely overlap but in a nontrivial way. I need to sample ...
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627 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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137 views

Estimate number of unique items by number of duplicates in a sample

We have a v. large (1e6) population with unknown number of types of items. We draw a small sample (~100) of a certain size, and find that exactly one item was duplicated. The question is to estimate ...
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138 views

How to estimate the given function using Rao Blackwellization approach?

I have a function $X$ which is lognormal (0,1) and then another function $\log Y = 4 + 2 \log(X) + \epsilon$ where $\epsilon \sim \mathcal N(0,1)$ I want to estimate $E(Y|X)$ as a Rao Blackwellized ...
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301 views

Gibbs sampling from full conditionals

I have the following joint density: $p(x_1,x_2,y_1,y_2) \propto \exp\left(−\left(x_1^2+x_2^2+c_1(y_2-y_1)^2+c_2(y_2-y_1)^4\right)\right)$ Can I use Gibbs sampling to sample from that? How can I get ...
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67 views

Random walk with restricted graph knowledge

I have a very large graph and a function of its vertices, and want to estimate mean value of this function. It's not possible to sample vertices uniformly in this problem, so a reasonable choice for ...
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309 views

Deriving priors for MCMC implementation

I have been working on an assignment lately wherein the object is to implement an MCMC approach to simulate from a generated posterior distribution. The posterior distribution is generated from a ...
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100 views

Averaged estimators in stochastic versions of EM

Recently I've been working EM algorithms for MAP estimation in a problem where the expectation is intractable, but the maximization is easy. Further, draws from the distribution in the E-step are ...
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1answer
23 views

What is the best way to report the results and uncertainty from a Monte Carlo simulation?

I am fitting data to a model that has ~30 input parameters, each with their own uncertainty levels, and which can interact with each other in the model. I therefore decided the best way to fit the ...
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17 views

Visualization of unbiasedness of high dimensional paramter estimates

Assume a statistical model $f_{\theta}(X)$ that allows to estimate a parameter vector $\hat{\theta}\in \mathbb{R}^p$ from data $X$ and assume that $p$ is high dimensional (you may assume something ...
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24 views

References for Texas Holdem

Does anybody know any good papers or software that use Monte Carlo techniques to estimate the probability of certain hands or winning/losing a hand in Texas Holdem? Ideally I'd like to have some ...
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43 views

Looking for a recursive formula for asymptotic variance of importance sampling estimator (self-normalized)

Looking for a recursive formula to approximate variance of importance sampling estimator $Var_q\big[\delta_{IS}\big]\approx\sum_{i=1}^n\tilde w(X_i)^2\big[h(X_i)-\delta_{IS}\big]^2$. This is an ...
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91 views

Hamiltonian Monte-Carlo in Reinforcement Learning

I was wondering if someone can point me out a reinforcement learning algorithm/paper (continuous variable), in which the Hamiltonian Monte-Carlo has been directly used. Thanks!
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1answer
90 views

Gibbs Sampling vs. Using Raw Probability in Contrastive Divergence

In Hinton's Practical Guide to Training Restricted Boltzmann Machines, Section 3, he discusses different situations in which one should take a sample from the Gibbs sampling process, and other ...
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392 views

Estimating standard error of Monte Carlo integration, non-MCMC version

Let us suppose that we're to evaluate the expectation of a random variable $h$ with respect to some distribution $\pi$, $\text{E}_{\pi}[h]$. The standard Monte Carlo estimate, using a sample of $X_1, ...
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119 views

Monte carlo method and Convergence in Distribution

Monte Carlo method, from what I could gather, allows one to obtain observations/draws from a possibly unknown statistical distribution. Let's say $T(X)\sim F$, where $T$ is a statistic, $X$ is a ...
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305 views

Importance sampling: what is this bias?

I am experiencing what seems to be a bias in importance sampling, which, given that it's an unbiased procedure, should not be there. Consider linear regression $$ y = X\beta+\epsilon $$ where there ...
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235 views

Convergence of gradient descent Monte Carlo Control with function approximation

Can anyone point me in the direction of a formal proof of convergence for a (on/off policy) Monte Carlo control algorithm with (non-)linear function approximation? In http://incompleteideas.net/book/...
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87 views

Error bars for sum of Monte Carlo integrations

I want to calculate a quantity $I$ which is the sum of integrals $I_k$, $$ I = \sum_k I_k\;,\quad I_k = \int_{\Omega} f_k(x)\,\textrm d x\;, $$ Every integral $I_k$ is evaluated independently by a ...
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116 views

sampling from a posterior derived from hierarchical Bayesian using HMC

I have a complex pdf based on hierarchical Bayesian formalism where x depends on the priors w'and w'', and I consider hyper-prior for the latter's as w=Php(zeta,beta) where Php stands for the hyper ...
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74 views

Sampling from distribution defined variationally

Suppose I define a probability distribution $\mu\in\mathrm{Prob}(\Sigma)$ over some compact $\Sigma\subseteq\mathbb{R}^n$ using a variational problem: $$ \mu:=\arg\min_{\mu\in\mathrm{Prob}(\Sigma)} F[\...
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59 views

Confusion on three “types” of Markov Chain Monte Carlo for the same inference

This is a long question but I would be very grateful if someone can help or provide some reference! And I believe this is a common confusion among beginners of MCMC. Background Given a directed ...
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723 views

Monte Carlo simulation for fitting distributions (Weibull and log-normal)

I am working on a computer project which needs statistical analysis and I am not much of a statistic person. I have a Bluetooth (BT) detector device which detects passing Bluetooth devices (i.e one ...
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73 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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203 views

MCMC for Maximum Entropy?

Is there a way to sample from a discrete probability distribution, whose distribution itself is the solution to a Maximum Entropy problem with known linear constraints, without needing to solve for ...
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1answer
92 views

How to explain simply that the set of runs for Non Intrusive Polynomial Chaos cannot be used as a Monte Carlo sample

I had quite an annoying problem at work, a few days ago. I was doing a forward Uncertainty Quantification analysis using Non Intrusive Polynomial Chaos (NISP) (see for example here). Basically, you ...
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105 views

Do Monte Carlo perturbations capture all the uncertainty in prediction?

I have a model $M$ that I use to predict a value $y = M(\vec x)$. I have known one-$\sigma$ error bars on each input $x_i \in \vec x$. I want to know the one-$\sigma$ error bar on my prediction $y$. ...
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83 views

Uniform convergence of Monte Carlo approximation

Usually Monte Carlo method is used to compute integration. For example, let $g(x,\theta)$ be a continuous function about $x$ and $\theta$, $f(x \mid \theta)$ is a continuous pdf with parameter $\theta$...
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209 views

How to show that the variance of Sequential Importance Sampling estimates increase with the dimension?

I am trying to understand the Particle Filter and the motivation to use it over the regular Sequential Importance Sampling. As far as I understand until now: 1- We try to estimate the expectation of ...
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259 views

Combining unbiased estimators with unknown variance

Say we are given a sequence of independently (but not identically) distributed random variables $X_1,...,X_n$ which are known to be bounded, $X_t \in (a,b)$, and to have the same mean, $\mathbb{E}X_t =...
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117 views

How to mathematically prove that we are sampling from same distributions?

The content of this question is about rigorously proving something which is otherwise considered easily correct intuitively. Let's assume we have a multivariate distribution $g(x_1,x_2,...,x_n)$ over ...
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142 views

Effect of each parameter on a Monte Carlo Simulation

I was wondering what is the best way to determine the effect of each random parameter on the result obtained from a Monte Carlo Simulation. I realise I have asked a similar question here, but this ...
3
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1answer
207 views

Selecting uncorrelated samples from a set of bulk data that contains correlated and dependent samples

i have a set of data that is generated by expensive computational model evaluations, on a total data set of 10000 samples in 40 dimensions. This sample data set is composed of different data sets, ...
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0answers
125 views

Relation between statistical randomness, uniform distribution and independence

In Monte Carlo simulation, we often consider how well a sequence of generated points are. If I am correct, one aspect is statistical randomness: A numeric sequence is said to be statistically ...
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84 views

Sampling in $\mathbb{R}^n$ with roughly equal Voronoi cells

N random points in a ball in $\mathbb{R}^n$ induce a Voronoi splitting or tessellation. Is there a way of random-generating points so that the volumes of the Voronoi cells are roughly equal ? This is ...
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115 views

Practical problems with difficult posteriors

I'm looking for difficult Bayesian inference problems to test out different Monte Carlo sampling methods. I've mostly been looking at Hamiltonian Monte Carlo based algorithms and in particular, I've ...

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