Unanswered Questions

16
votes
0answers
584 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: ...
16
votes
2answers
473 views

Stability of cross-validation in Bayesian models

I'm fitting a Bayesian HLM in JAGS using k-fold cross-validation (k=5). I'd like to know whether estimates of parameter $\beta$ are stable across all folds. What's the best way to do this? One idea ...
15
votes
1answer
259 views

When is binomial distribution function above/below its limiting Poisson distribution function?

Let $B(n,p,r)$ denote the binomial distribution function (DF) with parameters $n \in \mathbb N$ and $p \in (0,1)$ evaluated at $r \in \{0,1,\ldots,n\}$: \begin{equation} B(n,p,r) = \sum_{i=0}^r ...
13
votes
0answers
227 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 ...
13
votes
2answers
670 views

Gaussian Ratio Distribution: Derivatives wrt underlying $\mu$'s and $\sigma^2$s

I'm working with two independent normal distributions $X$ and $Y$, with means $\mu_x$ and $\mu_y$ and variances $\sigma^2_x$ and $\sigma^2_y$. I'm interested in the distribution of their ratio ...
11
votes
1answer
305 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 ...
11
votes
1answer
253 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 ...
10
votes
0answers
148 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 ...
10
votes
0answers
165 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 ...
10
votes
0answers
193 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
1answer
197 views

Interpretation of Bayesian 95% prediction interval

Assume the following bivariate regression model: $$ y_i = \beta x_i + u_i, $$ where $u_i$ is i.i.d $N(0, \sigma^2 = 9)$ for $i = 1,\ldots, n$. Assume a noninformative prior $p(\beta) \propto ...
9
votes
2answers
160 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 ...
9
votes
1answer
2k 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
2answers
82 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
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 ...

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