Inference, in a statistical context, refers to drawing conclusions from data containing an element of randomness introduced by e.g. measurement error, sampling variation, or assignment of experimental treatments. A common inferential paradigm is drawing conclusions about population parameters from ...

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Time Series Comparison - Correlation and Regression Model

I am trying to see if and how the news for affects the financial markets. I have a time-series for both of them. Should I standardise the series? I have a monthly return on prices from the Dow and a ...
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28 views

Should I use the t-test or the Wilcoxon rank sum test given these qqplots and Shapiro-Wilk stats [duplicate]

I have 4 groups and I want to test if the pairwise difference in means are significantly different. There are 6 pairwise differences. The QQnorm plots of the 4 groups look like this: The ...
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8 views

EM to Variational EM in LDA

Why exactly, when learning hidden variables distribution in LDA(Latent Dirichlet Allocation), one cannot use to the EM (Expectation Maximization) algorithm and have to resort to a variationnal EM ...
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12 views

Finding the underlying pdf by sampling “buckets” of values

The situation I'm looking at a system where I can perform the following trial: $N$ samples are randomly taken from a population of $V$ different values (which can be treated as categorical), ...
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47 views

Combining two probabilistic predictions

I am solving a machine learning task in which I need to predict a label $\tau$ from input $\vec x$. The input $\vec x$ can be considered as two parts $\vec u$ and $\vec v$ ($\vec x$ can be thought of ...
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99 views

Likelihood Ratio for the Bivariate Normal distribution

For a random sample from a Bivariate Normal distribution with $\rho=\frac{1}{2}$ and equal variances, i.e. $\sigma^2_x=\sigma^2_y=\sigma^2$, I would like to derive the Likelihood Ratio Test for the ...
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6 views

Probabilistc Inference for Hybrid Models

I am looking for a library that can solve (calculate the MAP estimate) of the variables in a probable graphical model in which some variables are discrete and some are continuous. I understand that ...
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13 views

Process interpretation of confidence intervals?

Frick (1998) explains how statistical inference can be interpreted as making causal claims about processes, without resorting to random sampling and infinite populations. This view seems particularly ...
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58 views

Connection between MLE (Maximum Likelihood Estimation) and introductory Inferential Statistics?

The first thing that one learns in statistics is to use the sample mean, $\hat{X}$, as an unbiased estimate of the population mean, $\mu$; and pretty much the same would be true for the variance, ...
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9 views

How to calculate the parameter value for a test with Item Response Theory?

Given a set of responses to a test with multiple choice I wish to analyse it with Item Response Theory: wikipedia on IRT. I am planing to use the 3PL (3 parameters) in the Item response function. How ...
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35 views

Inference about parameter $\theta$ be same?

Let $\mathbf x$ be a sample point and $T(\mathbf x)$ be a statistic of $\mathbf x$. Similarly, let $\mathbf y$ be a sample point and $T(\mathbf y)$ be a statistic of $\mathbf y$. In the book ...
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61 views

Example of sample $X_1,X_2,\ldots,X_n$

In the book Statistical Inference by George Casella, it is written that An experimenter uses the information in a sample $X_1,X_2,\ldots,X_n$ to make inferences about an unknown parameter $\theta$. ...
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16 views

Inference problem, potential testing methods

For a person who hasn't studied statistics thoroughly, but instead is only at entry to median level, when facing a hypothesis test/inference problem, how does she/he know all the potentially possible ...
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23 views

Confidence interval for a function of the MLE

I am studying an old assignment in which I have calculated the MLE for a sample from an exponential distribution. It then gives the formula for the median of an exponential distribution ...
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1answer
36 views

Problem with generalized likelihood ratio test from samples from beta distribution

I was trying to resolve this exercise: This exercise is from the book "Statistical Inference, Second Edition" by Casella and Berger. Checking the solutions manual, I was understanding the solution ...
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25 views

Limiting Distributions and Weak Law of Large Numbers

I have that $Y_1, Y_2, ..., Y_n$ are i.i.d. Poisson random variables with mean 1, and that $U_n = \sqrt{\frac{\sum_{i=1}^{n}{Y_i^2}}{n}}$. Given that I have a sequence $U_1, U_2, ..., U_n$, I'm ...
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13 views

Inference in bivariate continuous distributions

We have two nodes in different positions, which are represented by two random variables X,Y, with two prior bivariate continuous distributions, p_X , p_Y. f(X,Y,U,V) is a constraint on both ...
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18 views

Are daily updated data a sample or a population?

I want to do some tests based on all historical data of a product updated on a daily basis. These data are not supposed to have any time trend associated with them just be pulled on different days. I ...
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20 views

Indirect inference and p-value estimation

Let there be three continuous predictor variables X1, X2, and X3. Each variable is of length n. The correlation between the variables are rho12, rho13, and rho23. There is a binary outcome variable ...
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43 views

Does a lower t-stat suggest better evidence for rejection? [duplicate]

Say I have these two models: $y = \beta_0 +\beta_1x_1 + u$ $y = \beta_0 +\beta_1x_1 +\beta_2x_2 + u$ and the $p$ value for $H_0:\beta_1 = 0 $ with $\alpha = 10\%$ for both is less than 0.001, but ...
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73 views

How to do inference over two steps in a graphical model simultaneously?

I have observed data $D$ about a physical object described by $M$. I would like to determine the posterior distribution of $M$ given $D$, or $p(M|D)$. Now I can't infer this directly because unknown ...
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10 views

Estimating conditional probability of bernoulli data

Assume I have $i=1,\dots,N$ fathers, each with $j=1,\dots,n_i>0$ sons. Now there is a binary event $A_{i,j}$ with outcomes 1 and 0 and the respective probabilities $p$ and $1-p$. Now I want to ...
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12 views

Choosing which distribution is most accurate

Let's say we have two samples from different normal distributions and we want to determine which distribution is most accurate relative to an ideal value. How would we evaluate which one is more ...
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2answers
25 views

Observed and Observable

What is observed and what is observable? I found this two word frequently in the context of random variable and realization of ...
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28 views

Contaminated mark-recapture: estimating set size from sampled subsets

Someone poured marked balls in my urn! Simplistically, I think this is a capture-recapture problem where, after drawing and marking balls from the urn, somebody added an unknown number (approx 25% of ...
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A Question on Elementary Statistical Inference

A box contains $5$ white and $2$ black balls. A coin with unknown $P(Head)=p$ is tossed once. If it lands HEADS then a white ball is added, else a black ball is added to the box. Then a ball is ...
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Elastic/ridge/lasso analysis, what then?

I'm getting really interested in the elastic net procedure for predictor shrinkage/selection. It seems very powerful. But from the scientific point of view I don't know well what to do once I got the ...
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34 views

Is a coin fair? [duplicate]

Is a coin fair ? In other words, does a coin come up $50$% heads ? If a coin is unfair, then it would not come up $50$% heads. My thoughts : let's first identify the population and the parameter ...
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41 views

Estimating Size of a Set based on two Overlapping Subsets

I've searched everywhere for a similar question and many things come close but are not the same. I'm looking for a way to estimate the size of a set if two partially overlapping subsets are known ...
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2answers
35 views

Test if sampled data are randomly sampled

Is there a way to test if data are (or at least seem) randomly sampled? In other words, is there a way to measure if my data are randomly sampled -- instead of coming from a complex survey sampling ...
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24 views

How can I infer the joint distribution of an observed and a latent variable?

I have a dataset of school children with three features: Age $x$ of the student answering the survey Year group $a$ of the student answering the survey Year group $b$ of the best friend of the ...
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1answer
52 views

$H_0=250g$ and $H_1\neq 250g$" [closed]

We have a sample of size $100$ with a standard deviation of $5g$ It was decided that if the sample mean is between $245g$ and $255g$ while the sample average is $250g$ if $\mu=250g$ or $\mu\neq250g$ ...
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A Hypothesis Testing Question and Verification

Suppose we have two p.d.f.'s: $f_0(x)=1,$ if $0\leq x\leq1$, and $f_0(x)=0$ otherwise $f_1 (x)=2x$ if $0\leq x\leq1$, and $f_1(x)=0$ otherwise We want to test the hypotheses ...
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25 views

Kalman filter with input control noise?

assume we have a standard Kalman filter with input controls, following wikipedia notation (http://en.wikipedia.org/wiki/Kalman_filter) where the latent state is $x_{t}$ and the observation is $z_{t}$, ...
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29 views

Observed versus hidden variables for Bayesian network in this particular context

I am a novice in Bayesian networks. I have a problem which is best described (at least I think so) in the following story. One wants to predict earthquakes. Let's say it has 5 variables, the last one ...
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2answers
25 views

Inferring on an unknown number of function approximation

I want to ask whether a procedure to do the following job exists (or whether it makes sense for it to exist). First, assume we have $k$ functions $f_1,...f_k$ that have the same domain and range. ...
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17 views

Topic Model inference for subselection

Question: Does the inference of a trained topic model (LDA) used on a subselection of a text corpus result in more accurate document-document-relations? I used the MALLET-LDA Java-library to estimate ...
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1answer
25 views

Iteratively solving for prior probabilites.

I'm using Bayes theorem to classify data into two groups, where the conditional probability is known but the prior is not. So I assume that the ratio of prior probabilities is 1 and calculate the ...
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11 views

Perturbation analysis for expectation propagation

Consider the clutter problem of Tom Minka where the goal is to get posterior of the mean of one Gaussian component. The likelihood is a mixture of two Gaussians, one of which is just noise. The other ...
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52 views

Mean separation when interaction is significant

I am analyzing a factorial experiment in RCBD (3 cultivars x 4 inoculation methods with 10 replicates). All main effects and interactions are significant for a particular response variable. But in ...
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38 views

Test equality of coefficients in separate regressions when populations are not independent

I have three regressions with the same IVs. Equation 1: Y1 = X Equation 2: Y1 = X Equation 3: Y2 = X X is a vector of IVs with B1-B8 coefficients. Equations 2 and 3 are tested on the same ...
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2answers
106 views

AR(q) model with F-test

I am wondering that if we have an AR($q$) model for time series: $$X_i=\beta_1X_{i-1}+..+\beta_{p}X_{i-p} + \beta_{p+1} X_{i-p-1} +...+\beta_{q} X_{i-q}+\epsilon_i,\epsilon_i \;\text{iid}\; ...
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35 views

Gibbs sampling version for estimating the Dynamic Topic Model (DTM)?

The paper of Blei et Lafferty published at ICML'06 implements a (quite complicated) variational inference (VI) technique for estimating the parameters of the Dynamic Topic Model, see: ...
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14 views

Estimate posterior distribution for a group given aggregate data

I have data describing over a 15 million individuals where each item includes variables like these: A. Amount spent on airfare last year B. Brand of shoes C. Number of times visited some website in ...
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51 views

Reasoning for comparing variance between and within for Anova?

I looking for some logic reasoning why ANOVA test uses $σ^2$ given by these to variables. a logical reasoning why the ratio of variance between these two would say that the each population has the ...
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17 views

ABC-based inference for a dynamic model of multiple time stages

I am working on a dynamic model of multiple time stages (e.g. 0-15h, 15-30h, 30-45h); the model has three time stages in total. Each stage has associated with it 4-8 different parameters and I am ...
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405 views

Inference vs. estimation?

What are the differences between "inference" and "estimation" under the context of machine learning? As a newbie, I feel that we infer random variables and estimate the model parameters. Is my this ...
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142 views

Sufficiency or Insufficiency

Consider a random sample $\{X_1,X_2,X_3\}$ where $X_i$ are i.i.d. $Bernoulli(p)$ random variables where $p\in(0,1)$. Check if $T(X)=X_1+2X_2+X_3$ is a sufficient statistic for $p$. Firstly, how can ...
10
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164 views

Hypothesis Testing and the Scientific Method

Reading the answers to this thread, I started wondering about how Hypothesis Testing relates to the Scientific Method. While I have a good understanding of both, I am having a hard time drawing the ...
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40 views

Reparameterization of probability distribution (spike and slab)

I try to understand a statement in this paper: http://papers.nips.cc/paper/4305-spike-and-slab-variational-inference-for-multi-task-and-multiple-kernel-learning.pdf In particular, I am talking about ...