All Questions

69,070 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
28 votes
0 answers
2k views

How does a Relevance Vector Machine (RVM) work?

Relevance Vector Machines (RVMs) are really interesting models when contrasted with the highly geometrical (and popular) SVMs. In the light of a question like How does a Support Vector Machine (SVM) ...
user avatar
  • 15.7k
26 votes
1 answer
1k views

Bootstrapping Generalized Least Squares

Scenario: Consider the use of bootstrapping to estimate the distribution of model parameters fitted per a linear or nonlinear generalized least squares model. In particular, assume there is a ...
user avatar
24 votes
1 answer
582 views

Blind source separation of convex mixture?

Suppose I have $n$ independent sources, $X_1, X_2, ..., X_n$ and I observe $m$ convex mixtures: \begin{align} Y_1 &= a_{11}X_1 + a_{12}X_2 + \cdots + a_{1n}X_n\\ ...&\\ Y_m &= a_{m1}X_1 + ...
user avatar
  • 795
24 votes
0 answers
767 views

Distribution of inverse Wishart to a power?

In a related question, I had asked about the norm induced by an inverse Wishart matrix. I am interested in generalizing that result somewhat. Let $A\sim\mathcal{W}_p\left(I,n\right)$, a Wishart matrix ...
user avatar
  • 10.4k
20 votes
0 answers
873 views

Is there a general expression for ancillary statistics in exponential families?

An i.i.d sample $X_1,\dots,X_n$ from a scale family with c.d.f. $F(\frac{x}{\sigma})$ has $S(X)$ as an ancillary statistic if $S(X)$ depends on the sample only through $\frac{X_1}{X_n},\cdots,\frac{X_{...
user avatar
  • 2,270
20 votes
1 answer
872 views

Physical/pictoral interpretation of higher-order moments

I'm preparing a presentation about parallel statistics. I plan to illustrate the formulas for distributed computation of the mean and variance with examples involving center of gravity and moment of ...
user avatar
18 votes
0 answers
368 views

Empirical Bayes (In)Admissibility

Most of the time, sticking to a pure Bayesian approach to statistics with proper priors, leads to admissible estimators. Nevertheless, there is a good reason to use Empirical Bayes in many cases, and ...
user avatar
18 votes
0 answers
11k views

When should I use the Normal distribution or the Uniform distribution when using Xavier initialization?

Xavier initialization seems to be used quite widely now to initialize connection weights in neural networks, especially deep ones (see What are good initial weights in a neural network?). The ...
user avatar
  • 1,950
18 votes
0 answers
2k views

Implementation of CoVaR (a systemic risk measure) in R

I'm trying to estimate CoVaR using bivariate DCC GARCH in R. The concept of CoVaR is the dependence adjusted of VaR, which was first introduced by Adrian and Brunnermeier (2011). However, this ...
user avatar
  • 255
18 votes
0 answers
2k views

Picking block length in a block bootstrap

I am using the Mann-Kendall test to assess trends in a data time-series. I believe there is autocorrelation in my data and therefore need to use a block bootstrap to correct for it. I have plotted ...
user avatar
  • 181
17 votes
0 answers
1k views

Estimation of ARMA: state space vs. alternatives

I am interested in estimation of ARMA models. I understand that a popular approach is to write the model down in the state space form and then maximize the likelihood of the model using some ...
user avatar
16 votes
0 answers
3k views

Gamma hurdle model for continuous response?

I am modelling invertebrate.biomass ~ habitat.type * calendar.day + habitat.type * calendar.day ^ 2, with a random intercept of ...
user avatar
  • 261
16 votes
1 answer
716 views

Clustering & Time Series

I have a multivariate dataset that changes over time. I have extracted (and normalised) some features and used k-means to generate clusters over the entire span of the dataset. Now I want to see ...
user avatar
15 votes
0 answers
495 views

Asymptotic property of tuning parameter in penalized regression

I'm currently working on asymptotic properties of penalized regression. I've read a myriad of papers by now, but there is an essential issue that I cannot get my head around. To keep things simple, I'...
user avatar
  • 12.2k
15 votes
1 answer
474 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 ...
user avatar
  • 3,355
14 votes
0 answers
209 views

What is the "direct likelihood" point of view in statistics?

I am reading a Springer title from 1997 called Applied Generalized Linear Models by James K. Lindsey. In the preface, Lindsey writes For this text, the reader is assumed to have knowledge of basic ...
user avatar
  • 241
14 votes
0 answers
2k views

Rademacher complexity of logistic regression

Consider logistic regression. We have the logistic loss function, $\phi: R\rightarrow [0,1], \phi(u)=\log(1+\exp(-u))$, which is Lipschitz, and we have the linear function class $F=\{f_w:R^d \...
user avatar
  • 736
14 votes
1 answer
743 views

Visualizing many left-skewed distributions

I have a series of left-skewed/heavy tailed distributions that I would like to show. There are 42 distributions across three factors (labeled as A, ...
user avatar
  • 5,860
14 votes
0 answers
1k views

What is Shannon's source entropy?

Suppose that ${X_n; Y_n}$ is a random process with a discrete alphabet, that is, taking on values in a discrete set for $n$ data length. They correspond to the input and output of a communication ...
user avatar
  • 399
14 votes
0 answers
764 views

How can I measure model performance with weighted logistic regression?

I am working with some survey data that uses probability weights. A number of sources explain that likelihood-based tests and fit statistics like likelihood-ratio, AIC, and BIC are not valid in the ...
user avatar
14 votes
0 answers
1k views

Testing for a significant difference between ML estimates: Likelihood ratio or Wald test?

I am trying to test whether or not there is a significant difference between maximum likelihood estimates of two genetic parameters (selection and dominance) across two environments with genotype data ...
user avatar
  • 141
14 votes
1 answer
558 views

Are non-square latin hypercubes viable?

At https://github.com/OpenMDAO/OpenMDAO-Framework/issues/599 it is stated that non-square Latin Hypercube experimental design is not well defined (I assume that for higher dimensions that means ...
user avatar
  • 5,013
14 votes
0 answers
11k views

Time series regression with overlapping data

I am seeing a regression model which is regressing Year-on-Year stock index returns on lagged (12 months) Year-on-Year returns of the same stock index, credit spread (difference between monthly mean ...
user avatar
13 votes
0 answers
153 views

Why is Binning, Weight of Evidence and Information Value so ubiquitous in the Credit Risk/Finance industry?

In the credit risk industry (and finance industry as a whole, at least here in the UK), there is a very common and accepted 'proper' way to build scorecards. The general framework seems to be: ...
user avatar
13 votes
0 answers
575 views

Convolutional neural network for multi-variate time series?

I want to use CNN architectures for classification of multivariate time-series, where we apply one label to each sequence. I searched the net for the available designs in the literature and i found ...
user avatar
  • 429
13 votes
3 answers
638 views

Adjustments to (Linear Regression) Forecast

Full disclosure: I am not a statistician, nor do I claim to be one. I am a lowly IT administrator. Please play gentle with me. :) I am responsible for collecting and forecasting disk storage use ...
user avatar
  • 231
13 votes
0 answers
278 views

What is tantile regression?

My question follows on this discussion of medials and tantiles vs medians and quantiles from earlier this year: When would we use tantiles and the medial, rather than quantiles and the median? As ...
user avatar
  • 9,812
13 votes
1 answer
2k views

How to compare forecasting methods?

I have several intermittent data. Based on those data, I would like to compare several forecasting methods (Exponential Smoothing, Moving Average, Croston, and Syntetos-Boylan), and decide whether ...
user avatar
  • 131
13 votes
0 answers
5k views

Conditional expectation subscript notation

This should be a relatively simple question. I'm trying to confirm my understanding of the subscript notation on expectations when the subscript denotes a conditioning. In the example $$E_{Y|X}[(Y-f(...
user avatar
  • 882
13 votes
0 answers
388 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. ...
user avatar
  • 12.1k
12 votes
0 answers
597 views

Is the Wilcoxon two-sample test maximally powered to detect proportional odds alternatives?

We know from the literature that The Wilcoxon-Mann-Whitney two-sample rank sum test is optimal for detecting simple location shifts when comparing two continuous random variables that each have a ...
user avatar
12 votes
0 answers
738 views

what is the mistake of convergence proof in Adam

Sashank J. Reddi et. al in their paper "On the convergence of Adam and beyond" say that, Adam's proof of convergence as stated in original paper is wrong. More than that, they point out that the value ...
user avatar
12 votes
0 answers
571 views

Help me understand the Bayesian kernel density estimation (Sibisi and Skilling, 1996)

Sibisi and Skilling (1996, also mentioned in the 1997 paper) define Bayesian kernel density as $$ f(x) = \int dx' \,\phi(x')\, K(x, x') \tag{2} $$ Here the kernel $K$ is an assigned smooth ...
user avatar
  • 113k
12 votes
0 answers
3k views

What is the KL divergence of distribution from Dirac delta?

The Kullback–Leibler (KL) divergence of two continuous distributions $P(x)$ and $Q(x)$ is defined as $$D_{KL}(P \mid\mid Q) = \int_{X} P(x) \log{\left[\frac{P(x)}{Q(x)}\right]} dx$$ How can one ...
user avatar
  • 153
12 votes
1 answer
704 views

Bound the difference between Spearman's Correlation and Kendall's Correlation

I am trying to prove or disprove that the difference between Spearman's Correlation and Kendall's Correlation is no more than 1 (or less, the tighter the merrier). I am assuming there are no ties. ...
user avatar
  • 121
12 votes
0 answers
3k views

Interpreting and reporting gamm4 result

I am new to gam, and most of my knowledge comes from this document http://www3.nd.edu/~mclark19/learn/GAMS.pdf. Now I am using generalized addictive model with random effects to model some data, where ...
user avatar
  • 1,005
12 votes
2 answers
2k views

Scaling the backward variable in HMM Baum-Welch

I am just trying to implement the scaled Baum-Welch algorithm and I have run into a problem where my backward variables, after scaling, are over the value of 1. Is this normal? After all, ...
user avatar
12 votes
0 answers
1k views

Understanding Sequential Probability Ratio Test (SPRT) Likelihood Ratio

I am a software developer looking to develop an alternative for the simple hypothesis testing scheme described here. In short, the test works as follows: Two URLs are compared for their ability to ...
user avatar
  • 653
12 votes
0 answers
4k views

How to compare two distance matrices?

Suppose that I have two distance matrices for the same set of items. By a distance matrix I mean a square matrix whose (i,j)th entry holds the distance (in terms of cosine similarity) between ith and ...
user avatar
12 votes
1 answer
7k views

Confidence Intervals for AUC using cross-validation

I am analyzing the performance of a predictive model with the AUC, area under the ROC curve. I repeat several times cross-validation, and I have different estimations of the AUC in each folder. For ...
user avatar
11 votes
0 answers
823 views

Instrumental variables with interactions between endogenous variables

I have two endogenous variables $x_1$ and $x_2$ and am trying to estimate the following model: $$y = \theta_0 + \theta_1 x_1 + \theta_2 x_2 + \theta_{12} x_{12}$$ where $x_{12} = x_1\times x_2$. I'm ...
user avatar
  • 161
11 votes
0 answers
535 views

When can a Gaussian Process solve an SDE?

Considering an SDE of the form $$dX_t = \mu(X_t, t)dt + \sigma(X_t, t)dW_t ,$$ where $W_t$ is a Wiener process, is there a set of necessary and sufficient conditions on the structure of the functions $...
user avatar
  • 1,267
11 votes
0 answers
10k views

Deriving linear regression gradient with MSE

So I've been tinkering around with the backpropagation algorithm and to try to get a better understanding of how it works and my calculus is quite rusty. I've derived the gradient for linear ...
user avatar
  • 273
11 votes
0 answers
2k views

How to generate 2 correlated Beta random variables

I was wondering if it might be possible to generate 2 correlated $Beta$ random variables? In other words, I want to generate two Beta random variables which can be said to have come from two Beta ...
user avatar
  • 3,136
11 votes
1 answer
261 views

Correlation between two binary variables within one categorical variable

The Problem: I have measured two binary variables within 1 categorical variable with 5 levels. Initially, I thought I'd be able to use Fisher's Exact test or some $N \times M \times K$ version of it. ...
user avatar
  • 543
11 votes
0 answers
2k views

Is sparsity of topics a necessary condition for latent Dirichlet allocation (LDA) to work

I have been playing with the hyper-parameters of the latent Dirichlet allocation (LDA) model and am wondering how sparsity of topic priors play a role in inference. I have not performed these ...
user avatar
  • 3,032
11 votes
0 answers
1k views

Negative deviance explained by GAM with betareg in R

I am fitting the following model in "mgcv" package in R using option family=betar to predict a percentage cover response variable (...
user avatar
  • 443
11 votes
0 answers
258 views

Is autocorrelation not worth addressing with small N?

Consider a simple regression context in which there is a small set of response values, $Y$, and corresponding dates, $X$. (For simplicity, we can assume the dates are equally spaced.) We would like ...
user avatar
11 votes
0 answers
685 views

What approaches use multiple eigenvectors in graph spectral clustering?

Background: In Newman's PNAS 2006 paper Modularity and community structure in networks, the first eigenvector splits the graph in two clusters, and then each cluster can be further divided by ...
user avatar
11 votes
0 answers
2k views

Empirical Prediction interval for time series forecast based on quantile regression

As Gardner notes "almost all point forecasts are wrong", so prediction intervals (PI) are necessary to quantify uncertainty and help us make informed decisions. There exists theoretical PI, and in ...
user avatar
  • 7,399

15 30 50 per page
1
2 3 4 5
1382