26
votes
0answers
962 views

Variance on the sum of predicted values from a mixed effect model on a timeseries

I have a mixed effect model (in fact a generalized additive mixed model) that gives me predictions for a timeseries. To counter the autocorrelation, I use a corCAR1 model, given the fact I have ...
15
votes
0answers
450 views

SVD of correlated matrix should be additive but doesn't appear to be

I'm just trying to replicate a claim made in the following paper, Finding Correlated Biclusters from Gene Expression Data, which is: Proposition 4. If $X_{IJ}=R_{I}C^{T}_{J}$. then we have: ...
14
votes
0answers
404 views

In a multi-level model, what are the practical implications of estimating versus not-estimating random effect correlation parameters?

In a multi-level model, what are the practical and interpretation-related implications of estimating versus not-estimating random effect correlation parameters? The practical reason for asking this ...
12
votes
0answers
284 views

Mixed model vs. Pooling Standard Errors for Multi-site Studies - Why is a Mixed Model So Much More Efficient?

I've got a data set consisting of a series of "broken stick" monthly case counts from a handful of sites. I'm trying to get a single summary estimate from two different techniques: Technique 1: Fit a ...
9
votes
0answers
50 views

Training a basic Markov Random Field for classifying pixels in an image

I am attempting to learn how to use Markov Random Fields to segment regions in an image. I do not understand some of the parameters in the MRF or why the expectation maximisation I perform fails to ...
9
votes
0answers
175 views

How much smaller can $p$ values from ANOVA's $F$-test be vs. those from multiple $t$-tests on the same data?

Intro: Having noted the attention received today by this question, "Can ANOVA be significant when none of the pairwise t-tests is?," I thought I might be able to reframe it in an interesting way that ...
9
votes
0answers
121 views

Inference on fixed effects in a mixed effects model

I have correlated data and am using a logistic regression mixed effects model to estimate the individual level (conditional) effect for a predictor of interest. I know that for standard marginal ...
9
votes
0answers
234 views

Does a median-unbiased estimator minimize mean absolute deviance?

This is a follow-up but also a different question of my previous one. I read on wikipedia that " A median-unbiased estimator minimizes the risk with respect to the absolute-deviation loss function, ...
9
votes
0answers
189 views

Can the Mantel test be extended to asymmetric matrices?

The Mantel test is usually applied to symmetric distance/difference matrices. As far as I understand, an assumption of the test is that the measure used to define differences must be at least a ...
9
votes
0answers
3k views

How to estimate variance components with lmer for models with random effects and compare them with lme results

I performed an experiment where I raised different families coming from two different source populations, where each family was split up into a different treatments. After the experiment I measured ...
9
votes
0answers
193 views

Phylogenetic dependent variables: ANOVA?

I understand deriving a covariance matrix from phylogenetic data to make $cov(X,Y) = 0$ for two variables you're making a regression on. But what happens if you have one continuous variable, that ...
9
votes
0answers
306 views

Advice on identifying curve shape using quantreg

I'm using the quantreg package to make a regression model using the 99th percentile of my values in a data set. Based on advice from a previous stackoverflow question I asked, I used the following ...
8
votes
0answers
46 views

Incorporating more detailed explanatory variables over time

I'm trying to understand how I might best model a variable where over time I've obtained increasingly detailed predictors. For example, consider modeling recovery rates on defaulted loans. Suppose we ...
8
votes
0answers
168 views

Why the F-test in Gaussian linear models is most powerful?

For a Gaussian linear model $Y=\mu+\sigma G$ where $\mu$ is assumed to lie in some vector space $W$ and $G$ has the standard normal distribution on $\mathbb{R}^n$, the statistic of the $F$-test for ...
8
votes
0answers
185 views

VaR calculation

I am refering to this article: RiskMetrics Technical Document - Fourth Edition 1996, December One of their model is called RiskMetrics-GED and given by (p. 238-239): on p. 242 they say My ...
8
votes
0answers
253 views

Gaussian Like distribution with higher order moments

For the Gaussian distribution with unknown mean and variance, the sufficient statistics in the standard exponential family form is $T(x)=(x,x^2)$. I have a distribution that has ...
8
votes
0answers
1k views

How do you select variables in a regression model?

The traditional approach to variable selection is to find variables that contribute the most to predicting a new response. Recently I learned of an alternative to this. In modeling variables that ...
8
votes
0answers
878 views

How to analyse repeated measure ANOVA with three or more conditions presented in randomised order?

Context: My question concerns a typical design in my area – a researcher takes a group of subjects (say 10) and then applies three different conditions to them to measure the change in a response ...
7
votes
0answers
83 views

When optimizing a logistic regression model, sometimes more data makes things go *faster*. Any idea why?

I've been toying around with logistic regression with various batch optimization algorithms (conjugate gradient, newton-raphson, and various quasinewton methods). One thing I've noticed is that ...
7
votes
0answers
241 views

Ratio of probabilities vs ratio of PDFs

I'm using Bayes to solve a clustering problem. After doing some calculations I end up with the need to obtain the ratio of two probabilities: $$P(A)/P(B)$$ to be able to obtain $P(H|D)$. These ...
7
votes
0answers
1k views

Inverting the Fourier Transform for a Fisher distribution

The characteristic function of the Fisher$(1,\alpha)$ distribution is: $$C(t)=\frac{\Gamma \left(\frac{\alpha +1}{2}\right) U\left(\frac{1}{2},1-\frac{\alpha }{2},-i t \alpha \right)}{\Gamma ...
7
votes
0answers
120 views

Paper on performing hypothesis tests based on outcome of another test

It is well known that it is problematic to choose a statistical test based on the outcome of another statistical test, as the p-values are difficult to impossible to interpret (e.g. Choosing a ...
7
votes
0answers
121 views

Bound for Arithmetic Harmonic mean inequality for matrices?

NOTE: This question has originally been posted in MSE, but it did not generate any interest. It was first posted there, because the question itself is a pure matrix-algebra question. Nevertheless, ...
7
votes
0answers
143 views

Issues with ordinary kriging

I was following this wiki article related to ordinary kriging Now my covariance matrix looks like this, for 4 variables ...
7
votes
0answers
153 views

p-value adjustment for Local Moran's I statistic (LISA)

I'm working with some exploratory spatial analysis in R using spdep package. I came across an option to adjust p-values of local indicators of spatial association (LISA) calculated using ...
7
votes
0answers
179 views

Unique (?) idea for forecasting sales

I'm working on developing a model to predict total sales of a product. I have about a year and a half of bookings data, so I could do a standard time series analysis. However, I also have a lot of ...
7
votes
0answers
94 views

Testing certain contrasts: Is this provably a hard problem, or not?

I posted this to mathoverflow and no one's answering: Scheffé's method for identifying statistically significant contrasts is widely known. A contrast among the means $\mu_i$, $i=1,\ldots,r$ of $r$ ...
7
votes
0answers
100 views

Tail bounds on Euclidean norm for uniform distribution on $\{-n,-(n-1),…,n-1,n\}^d$

What are known upper bounds on how often the Euclidean norm of a uniformly chosen element of $\:\{-n,~-(n-1),~...,~n-1,~n\}^d\:$ will be larger than a given threshold? I'm mainly interested in bounds ...
7
votes
0answers
79 views

Analyze a football match: similar players with DBSCAN and similar trajectories with TRACLUS

I'm trying to analyze a dataset that originates from sensors located near players' shoes in a match (http://www.orgs.ttu.edu/debs2013/index.php?goto=cfchallengedetails). I decided to look at ...
7
votes
0answers
229 views

Clustered standard errors vs. multilevel modeling?

I've skimmed through several books (Raudenbush & Bryk, Snijders & Bosker, Gelman & Hill, etc.) and several articles (Gelman, Jusko, Primo & Jacobsmeier, etc.), and I still haven't ...
7
votes
0answers
209 views

Luce choice axiom, question about conditional probability

I'm reading Luce (1959). Then I found this statement: When a person chooses among alternatives, very often their responses appear to be governed by probabilities that are conditioned on the ...
7
votes
0answers
148 views

AIC/BIC: how many parameters does a permutation count for?

Let's say I have a model selection problem and I am trying to use AIC or BIC to evaluate the models. This is straightforward for models that have some number $k$ of real-valued parameters. However, ...
7
votes
0answers
171 views

Rao-Blackwellization of sequential Monte Carlo filters

In the seminal paper "Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks" by A. Doucet et. al. a sequential monte carlo filter (particle filter) is proposed, which makes use of a ...
7
votes
0answers
132 views

Penalized spline confidence intervals based on cluster-sandwich VCV

This is my first post here, but I've benefited a lot from this forum's results popping up in google search results. I've been teaching myself semi-parametric regression using penalized splines. ...
7
votes
0answers
1k views

R and EViews differences in AR(1) estimates

The main problem is: I cannot obtain similar parameter estimates with EViews and R. For reasons I do not know myself, I need to estimate parameters for certain data using EViews. This is done by ...
7
votes
0answers
154 views

Can I use optimally scaled variables for a factor analysis to account for rotation? If I can then how?

I have discussed this issue several times in this site, but I am asking it again for a final justification from the experts of our community. I wanted to extract four factors (I should call dimensions ...
7
votes
0answers
289 views

Calculating prediction intervals when using cross validation

Are standard deviation estimates calculated via: $ s_N = \sqrt{\frac{1}{N} \sum_{i=1}^N (x_i - \overline{x})^2}. $ (http://en.wikipedia.org/wiki/Standard_deviation#Sample_standard_deviation) for ...
7
votes
0answers
188 views

$ARIMA(p,d,q)+X_t$, Simulation over Forecasting period

I have time series data and I used an $ARIMA(p,d,q)+X_t$ as the model to fit the data. The $X_t$ is an indicator random variable that is either 0 (when I don’t see a rare event) or 1 (when I see the ...
7
votes
0answers
256 views

What are the options in proportional hazard regression model when Schoenfeld residuals are not good?

I am doing a Cox proportional hazards regression in R using coxph, which includes many variables. The Martingale residuals look great, and the Schoenfeld residuals ...
7
votes
0answers
749 views

Random forests for multivariate regression

I have a multi-output regression problem with $d_x$ input features and $d_y$ outputs. The outputs have a complex, non-linear correlation structure. I'd like to use random forests to do the ...
7
votes
0answers
272 views

Dynamic factor analysis vs factor analysis on differences

I'm trying to wrap my head around dynamic factor analysis. So far, my understanding is that DFA is just factor analysis plus a time series model on the scores (the loadings remain fixed). However, in ...
7
votes
0answers
527 views

Would a Random Forest with multiple outputs be possible/practical?

Random Forests (RFs) is a competitive data modeling/mining method. An RF model has one output -- the output/prediction variable. The naive approach to modeling multiple outputs with RFs would be to ...
7
votes
0answers
233 views

Updating classification probability in logistic regression through time

I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
7
votes
0answers
1k views

How to analyze longitudinal count data: accounting for temporal autocorrelation in GLMM?

Hello statistical gurus and R programming wizards, I am interested in modeling animal captures as a function of environmental conditions and day of the year. As part of another study, I have counts ...
7
votes
0answers
1k views

Split-split-plot design and lme

I’m working on a data set in order to evaluate the impact of drying on sediment microbial activities. The objective is to determine if the impact of drying varies among sediment types and/or depth ...
7
votes
0answers
378 views

What data and statistics skills are currently in high demand and where are they in high demand?

I have a job doing data analysis in finance. My current job is such that I don't have much exposure to things happening in the rest of my industry or other industries. I have a fair amount of ...
7
votes
0answers
615 views

Intraclass Correlation Coefficients (ICC) with Multiple Variables

Suppose I have measured some variable in siblings, which are nested within families. The data structure looks like this: family sibling value ------ ------- ----- 1 1 y_11 1 2 ...
7
votes
0answers
811 views

How to use G Power 3 to calculate statistical power in mixed design ANOVA with unequal group sample sizes

In G power 3, ANOVA repeated measures within-between interaction: Only the total sample size is reported assuming equal sample size for the two groups. My questions are: How would it work if the ...
7
votes
0answers
464 views

How can I assess GEE/logistic model fit when covariates have some missing data?

I have fit two generalized estimating equation (GEE) models to my data: 1) Model 1: Outcome is longitudinal Yes/No variable (A) (year 1,2,3,4,5) with longitudinal continuous predictor (B) for years ...
6
votes
0answers
176 views

What does $(X'X)^{-1}$ mean?

In a regression what is the matrix $(X'X)^{-1}$? what do its interior elements represent? Can anyone tell me which values in a stata regression are represented by $(X'X)^{-1}$?

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