All Questions

1
vote
0answers
3 views

Probability of sparse spectrum

Consider a vector $v$ such that $v \sim \mathrm{Unif}(\mathbb{S}^{d-1})$, the uniform distribution on the unit sphere in $d$ dimensions. Question: is there an upper bound on the probability that $v$ ...
0
votes
0answers
6 views

Is this a crossover design?

I am working with collaborators who are conducting an education research study to see if there is a difference in learning outcomes between two learning experiences, one with a technology tool (let’s ...
0
votes
0answers
5 views

What is an appropriate technique for large number of correlated predictor variables with interactions?

I want to allow the effects of a large number of continuous predictor variables to be different depending on which treatment group the individual is a part of. If I had only three continuous ...
0
votes
0answers
3 views

Longitudinal analysis of incidence rates

I am wondering how to conduct longitudinal analysis of incidence rates. A population was followed 5 years (2001-2005), and in each year "person-years" and "event" were calculated. Now I am ...
0
votes
0answers
5 views

Approximating Categorical Distribution with Mixture of Normals

I have a categorical distribution, and I would like to approximate it using a mixture of normals. Is there any way to do this simply? I've seen an example on how to use a multivariate normal to do ...
1
vote
0answers
12 views

Distribution of the Sum of an AR(1) Model Time Series

I have the following model for my model $\Delta X_{t} = \mu \Delta t + \rho \Delta X_{t-1} + \sigma \sqrt{\Delta t} Z_t$ with the following initial conditions - $\Delta X_{1} = \mu \Delta t + \...
0
votes
0answers
3 views

GMM estimator: Two-step vs. Iterated estimator

I'm currently trying to understand the differences between the two-step efficient GMM estimator, and the Iterated GMM estimator. As I understand the T-S, is based on the First-step and depends on the ...
0
votes
0answers
10 views

Gaussian process - Why adding data points cannot increase the predictive bias?

I've seen this question here: How to increase variance in Gaussian Process regression? But a proof isn't provided. I'm looking at this book: Rasmussen Williams 2006 Gaussian processes for machine ...
0
votes
0answers
7 views

Cross-validation error of ridge regression

Problem In order to find the optimal parameter $\lambda$, each individual observation is taken out from design matrix $\mathbf{X}$ and solves $$ \text{minimize}_{\beta} \frac{1}{2}\Vert \mathbf{y}_{-...
1
vote
1answer
12 views

Sequence of shifted exponential distributions has uniform conditionals?

Suppose we generate a sequence of random variables as follows. First, we let $X_1 \sim Exp(\lambda)$, where $Exp(\lambda)$ denotes the exponential distribution with rate parameter $\lambda>0$. For $...
0
votes
0answers
4 views

Correct calculation of repeated cross-validation classification metrics

We can obtain a resampled estimate of training set classification accuracy from caret::confusionMatrix.train(model) e.g., ...
0
votes
1answer
16 views

Bootstrap Confidence Bands for Linear Regression (in R)

I am looking for a way to implement non-parametric bootstrap to confidence bands around my regression line for my linear regression model. I am, however, new to bootstrap, therefore I am unsure how to ...
0
votes
0answers
3 views

Pool redundancy analysis results from multiple imputations of missing data

I have a dataset that includes missing values, and I would like to carry out redundancy analysis using multiple imputation to fill in the missing values. So far, I have successfully created multiple ...
0
votes
0answers
4 views

Dealing with Endogeneity in a Logit Regression when the Endogenous Regressors are Discrete

I would like to estimate a logit model in the presence of endogeneity. The dependent variable is binary (actually, it is non-binary with multiple ordinal categories, but from what I've read dealing ...
1
vote
1answer
21 views

Gradient Descent Rule in feedforward ANN

I am having a hard time understanding the Gradient Descent Rule for learning in a feedforward ANN. In particular, how do we determine the initial weight vector, and how is this weight vector adjusted ...
3
votes
0answers
17 views

Convergence rate of the inverse covariance matrix

I am trying to find results regarding the convergence rate of the inverse covariance matrix in the case where the number of observations $n$ is larger than the number of dimensions $p$. Assume that $...
0
votes
3answers
39 views

Global p value in multivariate linear regression in R

I am using multivariate linear regression to see association between length of hospital stay (Dependent Variable) and few predictors (Independent variables). All the predictors are categorical ...
4
votes
1answer
31 views

Classifier which minimizes inaccuracy

I recently interviewed for a machine learning job which involved very mathematically rigorous questions. This is one of them, which I'm still very confused about. Question: Given a data generating ...
1
vote
0answers
20 views

Cross validation decreases precision?

I've been working on a simple logistic regression model and I'm trying to improve its precision by cross validation. This is the code I've done so far (without including the imports): ...
0
votes
0answers
13 views

what is the difference between a multilayered autoencoder and a hierarchical latent variable model?

I have been trying to understand how hierarchical latent variable models are different from multilayered autoencoders and in specific the argument below Autoencoder networks resemble in many ways ...
0
votes
0answers
11 views

comparing mean detection rate - t test or something else? [on hold]

I am wanting to compare the mean detection rate between two groups of people. A dummy dataset is below. It is based on whether or not a disease is detected (1 = detected) in patients (4 different ...
0
votes
0answers
20 views

Statistically evaluating classification accuracy of machine learning model

Let's say I'm trying to evaluate a classification algorithm and suppose there are $m$ data points in my test set. Here's my understanding so far: assuming my evaluation metric is the classification ...
1
vote
0answers
25 views

Should I use Poisson or Binomial distribution to solve this question? [on hold]

My question goes as below: A major warehouse facility has 10 semi-trailer loading bays, which can all be used simultaneously. On average only 7 bays are in use. a. What is the probability that all ...
0
votes
0answers
14 views

Sample Bias Correction: What is the correct methodology? [on hold]

I have a sample of people (about 1/3 of the population of one large city) whose home is geolocated to the county level. This is the marketshare of a company. There is another big player in the same ...
0
votes
1answer
23 views

Z-scores for different size groups

I want to know how I can calculate the Z-scores for groups with different sizes? Let me try to explain: We have a city with 100.000 inhabitans. The city is divided in 10 neighborhoods, all with ...
0
votes
1answer
27 views

Recurrent Neural Network vs Traditional Neural Network

I've read a lot about the difference between RNN and traditional NNs (MPLs) but I have still doubts. Below I would like to ask a specific question. Assume that we have a sequence data: $s_1, s_2, s_3,...
0
votes
0answers
8 views

Can a ratio of performance be used to measure dependence and assign weights in a weighted average?

With only a modest grasp of inferential stats and maths in general, I've been wondering how one might derive the weights for a weighted average from a variable that isn't as straightforward as a ...
0
votes
1answer
6 views

Why margins and mfx yield different results in R?

When I run a simple logit regression between a binary variable $y$ over another binary variable $x$, the average marginal effects obtained by the function logitmfx (...
0
votes
0answers
21 views

Developing an appropriate volatility variable to predict stock returns based on past month

I am doing a project about the predictability of stock returns. I am using following regression model: \begin{equation} r_{t} = \alpha+\beta X_{t-1}+\epsilon_{t}, \end{equation} where $r_{t}$ is the ...
0
votes
0answers
17 views

Covariance of a square of a normal random variable (X^2) and another normal random variable (Y) [on hold]

Find Cov(X^2,Y) if X and Y are normal random variables with N~(0,1) and Cov(X,Y)=c.
0
votes
0answers
5 views

Finding interesting subsets of a population - Facet Recommendation

I'm looking for the type of maths/stats to recommend facet selection to users. Let's say I have a dataset eg Person, Language, Age, Income, Suburb (i.e. a combination of numeric, continuous data and ...
0
votes
0answers
36 views

Derivation of the LSTM Backpropagation equations

From the Coursera Specialization in Deep Learning come the following LSTM backpropagation equations: However, my derivations lead to different conclusions: Please note that in the aforementioned ...
0
votes
1answer
15 views

How to code effect modifier in a Cox Regression using R?

The definition of the distinction between the effect modifier and interaction term is: Interaction and effect modification are formally defined within the counterfactual framework. Interaction is ...
0
votes
0answers
5 views

GAM discrete time survival prediction in R

So i've been trying to perform a discrete time survival analysis in R. I have been using the 'discSurv' package to generate the augmented data matrix for the full dataset and performed an stratified ...
0
votes
0answers
8 views

Interrogating the results of the Markov simulation - Help and feedback highly appreciated

0 I have built a Markov chain with which I can simulate the daily routine of people (activity patterns). Each simulation day is divided into 144-time steps and the person can carry out one of ...
0
votes
0answers
8 views

Interpreting regression coefficients with cube root transformation of both dependent and independent variables

I have used the cube root $(1/3)$ transformation on both my dependent and one of my independent variables. I would have preferred a log-transformation but my data has both negative values and zeroes. ...
0
votes
0answers
8 views

Derive signals from a signal vector using a mixing matrix

I am tyring to decompose a noisy vector into a sum of signals. Say we have $s$ independent signals and $c$ channels. Each signal can lead to an increase of output in some, but not all of the channels ...
0
votes
0answers
9 views

What does the associate editor mean about my sample sizes? [on hold]

The associate editor have a question about my paper. He said "In the Monte Carlo you assume that there are 600 low frequency observations, which seems heroic. What are the sample sizes considered in ...
0
votes
0answers
8 views

Logistic Mixed-effect Regression: How to have a meaningful fixed intercept parameter?

I have a study where participants view 10 faces and have to guess their first names between 2 options (1 correct/1 wrong). There are 2 between-subjects versions of the faces (the faces are different ...
0
votes
1answer
11 views

Does the threshold value of a logistic regression hypothesis has an effect on the accuracy?

It is true that the threshold value of a logistic regression hypothesis has an effect on the Precision/Recall metrics. Suppose you have trained a logistic regression classifier which is outputting $...
0
votes
0answers
5 views

Comparing hazard function of subset and whole data

Is there a way to compare the hazard function that comes from a stochastic process with the hazard function which comes from a subset of that process? Simulations of a stochastic process generate ...
0
votes
0answers
11 views

What test to use to compare two proportions (and calculate effect size and confidence interval)?

There are many related questions here and elsewhere, but I found no satisfying answer. There are plenty of related tests and concepts: Z-test, chi-squared test, G-test, McNemar's test, Fisher's exact,...
2
votes
1answer
24 views

Monte Carlo test for statistical significance of typhoon passage frequency

This question is related to this post: https://stackoverflow.com/q/56288002/6638232 Basically, I am trying to perform a significance test using Monte Carlo simulation but I am having a problem in ...
0
votes
1answer
46 views

Validity of Weibull distribution

I have come across validation engineers picking the Weibull distribution as a way to generate test stimulus. When they do this, they seem to chose the parameterisation without reference to any ...
0
votes
1answer
22 views

Coefficient Interpretation when dependent and independent variables are percentages

I have built a linear mixed regression model with fund returns (measured in percentage ie. 0.01 denotes one percent) as the dependent variable. For the independent variables I have percentage level of ...
0
votes
0answers
4 views

Lars alphas_ results

Could any one explain how the results on alphas_ attribute in Lars model are calculated? In the definition: alphas_ is the maximum covariance (abs value) in each iteration. But when I look into ...
0
votes
0answers
10 views

How to generate and correlate more than two random variables which are from different distributions given then correlation matrix? [duplicate]

I tried to fit some variables using the non-parametric method(kernel smooth), so those distribution for each variable are different,so cholesky descomposition won´t work for this case. Is there some ...
0
votes
0answers
3 views

Selection smoothing parameter for using function SPM(library SemiPar)

Suppose i fit a model of the following form: ...
1
vote
0answers
22 views

Features with missing entries are different in train data than in test data

I know there is a number of approaches to preprocess training data with missing entries: dropping features, imputing mean values, etc. I've compared few of such approaches and found that dropping ...
0
votes
0answers
4 views

Does Sørensen–Dice Coefficient (Dice Score) only account for true positives?

I'm working in a project on medical image segmentation which uses the Dice Score as part of the loss function, but I got some doubts with the commonly adopted implementation. The definition of Dice ...

15 30 50 per page