0
votes
0answers
2 views

What's the relationship between the generalized squared multiple correlation and SEM explained variance?

I am testing this model. I also ran the same analysis as two multi-step regressions. The results came out like this: Applying the formula for a generalized squared multiple correlation, I get: ...
0
votes
0answers
4 views

SVD and eigendecomposition for a symmetric square matrix

As far as I know, SVD and eigendecomposition give the same result for symmetric square matrices. But when I check the results in R, that's not what I see. Please see below R code (I set the random ...
0
votes
0answers
5 views

Issues with derivative of a copula density

Suppose I have a bivariate copula density with marginals F(X) (F(X) is normal with parameters mu1, sigma1^2) and G(Y) (G(Y) is normal with parameters mu2 and sigma2^2). I want to take a derivative of ...
0
votes
0answers
8 views

Random Forest Classifier returns oob_score of 0?

I have ~110 columns with ~2000 rows and I feel like something is off it takes 15 minutes when n is 500 and the oob_score_ returns 0? What could be going wrong? ...
0
votes
0answers
3 views

L-Kurtosis calculation

I am doing statistical analysis on some signal data and after some reading was thinking that L-kurtosis would be a good numerical value to use in differentiating delta trains and sine waves with ...
0
votes
0answers
5 views

Help explain the “redundancy” of canonical correlation

I am reading a material about canonical correlation and it introduces a concept named "redundancy". I have been puzzled for one day but still could not get a understanding. The following is a screen ...
0
votes
0answers
13 views

PCA on a rank-deficient matrix using SVD?

I have a high-dimensional data matrix X where sample size is smaller than the variable size. I want to use PCA as a dimensionality reduction method, but I cannot ...
0
votes
0answers
4 views

Reference for rigorous derivation of bigram model

The unigram model for bodies of text makes the assumption that in a given corpus the value of the $n$th word is independent of the $n-1$th word. Then, for a fixed dictionary $D$ and a corpus of text ...
0
votes
0answers
7 views

Are these models nested?

Are a standard Gaussian and a skew Gaussian nested? I'd say yes, because when we set the skewness parameter $\alpha=0$ in the skew normal we get the standard Gaussian. Also, are the normal/skew ...
0
votes
0answers
7 views

Interpreting the result of decomposing time series

I don't have a lot of experience working with time series data. Now I have a 3 year, monthly data for several entities (you can think about them as different stores), that I would like to do some ...
0
votes
0answers
4 views

How should items be order in a bar chart comparing items in two general categories?

The following chart compares two types of computational workloads based on six aspects of their interaction with the memory system. While it is obvious that individual benchmarks should be grouped ...
0
votes
0answers
5 views

Using simulated data to check when patterns in GLMM residual plots are acceptable

I have run the following Poisson GLMM: ...
0
votes
0answers
8 views

How to find p value range for two sample test given only sample size and standard deviation? [on hold]

Given the sample size of two samples and their standard deviations, I could not find their exact p score, but should be able to find a range. However, I am having a very hard time determining how to ...
0
votes
0answers
9 views

Different Methods for clustering skills in text

Consider a talent pool in which each member has some set of skills. Some of these talent are submitted to orders as potential candidates of which one is selected. It is reasonable to assume that the ...
0
votes
0answers
8 views

Is it viable to apply Perason/Spearman correlation to a slightly non-monotonic relationship?

Is it viable to use Pearson/Spearmans correlation here? If the answer is no, would it be viable when getting rid of the first and the last points were the drove obviously drops steeper. The drops ...
0
votes
0answers
4 views

Are there any measures of Nonspecificity that take into account unreachable states?

The Hartley function, the main measure of Nonspecificity, is essentially based on the count of all possible states. However, while coding the Hartley, I realized that "possible" means all remaining ...
0
votes
0answers
7 views

Component score covariance matrix [on hold]

What does the component (factor) score covariance matrix in PCA or FA explain?
1
vote
1answer
47 views

How many doors does a salesman have to knock before reaching x sales?

Imagine a salesman assigned to a neighborhood, each home has a unique and independent conversion rate associated with it that we might model like ...
0
votes
1answer
28 views

How to use cross-validation with regularization?

I think I understand each of these concepts (cross-validation, regularization) independently, but I'm not quite clear on how they can be put together in practice. Loosely speaking, in ...
0
votes
0answers
15 views

Modelling combined linear and quadratic age effects

I am running a GLM (Type III) with several predictors, including age and age squared as predictors. I am interested in knowing the combined effect size and p-value of age+age^2, since neither is ...
2
votes
0answers
26 views

How to simulate more data for machine learning?

I am attempting to analyze a small dataset using machine learning (SVM, binary problem). There are $103$ samples and $215$ variables (all variables are real numbers). Some of the variables (around ...
2
votes
1answer
18 views

Standard Error of Ratio of Weibull Distributions

Assuming that I have 2 distinct random variables that follow a weibull distribution, what's the standard error* of the ratio distribution of these 2 random variables? Basically I have X ~ weibull, Y ...
2
votes
1answer
15 views

Are results from fixed effects models generalizable?

Here's a statement I read from the method section in a paper: "One disadvantage of the fixed-effects approach is that the results obtained are conditional on the data used to estimate them; that is, ...
1
vote
0answers
18 views

Lasso - Representing l1-ball constraint using the penalized formulation

I would like to solve the following problem: $$ \beta = \arg\min_{\beta;\|\beta\|_1 \leq1} \|X\beta-y\|_2^2 $$ which happens to be the constrained formulation of the Lasso, considering only ...
1
vote
2answers
26 views

Difference between rexp and qexp in R

I need to write a simulation that requires the use of exponential distribution. I was wondering what is the difference between the following two approaches in drawing random numbers from an ...
0
votes
0answers
8 views

SVM always predicts same label

I have 11 labels. I trained an SVM model: ...
1
vote
2answers
26 views

Implement cross validation for a prediction model

I am trying to assess the predictive performance of two competing linear regression models. $$ model 1: Y \sim X_{1} + X_{2}$$ $$ model 2: Y \sim X_{1} + X_{2} + X_{3}$$ where y is continuous. I ...
0
votes
0answers
17 views

Proof of Algebraic Formula for the Dice Toss Total

To figure out exactly the expected frequency of a given sum in a dice toss (given a certain number of dice and sides/dice), the following formula is posted here by @Glen_b (adapted to dice of six ...
0
votes
0answers
6 views

Interpretation results seasonality in data R

I have a question about the results that I get from checking whether my data contains seasonality or not. I have a csv file which contains date, period and year. However, R reads the date as a factor ...
0
votes
0answers
16 views

What is canonical r squared?

I know r-squared is the the percent of variance explained by a model. I am currently reading materials about canonical correlation and found a new concept "canonical r squared". The material does not ...
2
votes
0answers
23 views

Can I combine 10 variables into one variable before performing logistic regression on 18 total variables?

Univariate analysis of 18 variables possibly associated with spine infection--can all the historical variables be combined into one variable, then logistic regression be performed?
1
vote
0answers
5 views

A question on notation in variational message passing

This paper introduces variational message passing. Formula (8) is based on Fig 1. Formula (a) is $\ln Q^*_j(H_j)=\langle\ln P(H_j\mid\vec{pa_j})\rangle_{\sim Q(H_j)}+\sum_{k\in ch_j}\langle\ln ...
0
votes
0answers
3 views

change co-variance structure for linear quantile mixed model for animal breeding

I'd like to analysis my data (animal breeding) with linear quantile mixed model. Lqmm package in R does that but co-variance structure do not know A (relationship numerator matrix is Sparse matrix) ...
0
votes
0answers
11 views

Nonlinear dimensionality reduction (sample size is smaller than number of features)

One question for the nonlinear dimensionality reduction. I have 800 samples and 4900 features for a regression problem, 80% for training and 20% for testing. I have tried linear PCA to reduce it to ...
0
votes
0answers
17 views
0
votes
0answers
20 views

Non linear optimization in R [on hold]

I am working on a non linear optimization problem and the packages I have been trying to use are alabama Rsolnp and nloptr. But in each case I seem to be getting the same kind of error where I am ...
0
votes
0answers
18 views

markov chain question [on hold]

There are two points which are A and B. The distance between A and B is 50meter. One person goes to A with probability 1/6, he goes to B with probability 3/6. And he goes nowhere with probability 2/6. ...
0
votes
0answers
16 views

Deriving errors for fitted parameters using Monte Carlo

I have the following data: One 2D image, each of its pixels is a measurement. I will call this "data map". One 2D image, each of its pixels is the error (1 sigma) of the above measurements. I will ...
0
votes
0answers
23 views

Understanding lm() function in R with weights

Consider the following simplified dataset (sales and percent of color-type sales by region): ...
0
votes
0answers
16 views

anomaly detection with Markov chain

The paper uses a simple technique to detect intrusions in computer systems. I will briefly explain it and ask a question: The paper proposes a simple 1-order Markov chain modelling approach to detect ...
0
votes
0answers
11 views

Input EGARCH model (idiosyncratic volatility)

I have a time-series of historical volatility observations. I want to use an EGARCH model because I believe it is a better representation of the behaviour of these volatilities. Can I estimate an ...
1
vote
0answers
13 views

mixed model with non-normally distributed data

I have a database in which a group of patients was assigned to one of two treatment arms. I have to find out if there is a difference in the evolution of a particular biomarker between these two ...
0
votes
0answers
5 views

Is it possible to apply a weight against multiple attributes in Rattle?

Hi I'm trying to figure out how to apply weight to multiple attributes in Rattle. I'd basically like SVM or random forest models to give greater weighting to ...
0
votes
0answers
21 views

KS, RMSE tests in R

I have a set of yearly peak river flows and I am trying to use the KS test to conclude if the data is coming from a generalized extreme value (GEV) distribution. I am also trying to calculate a root ...
2
votes
1answer
22 views

Prior predictive density given by $f(y) = {f(y\mid \lambda) g(\lambda)}\big/{g(\lambda | y)}$?

(I guess stats.SE is the right place for this) I'm reading Albert's book "Bayesian computation with R". To get theprior predictive density, he extensively uses this formula $$f(y) = \frac{f(y\mid ...
1
vote
0answers
29 views

Lme4 and lmertest: Different degrees of freedom from same dataset

I just encountered a problem while analyzing experimental data using lme4 and lmertest. In the experiment, 67 subjects gave 3 ratings for 50 stimuli shown for 3 different durations (a total of 10050 ...
0
votes
0answers
14 views

Data augmentation techniques for general datasets?

In many machine learning applications, the so called data augmentation methods have allowed building better models. For example, assume a training set of $100$ images of cats and dogs. By rotating, ...
1
vote
0answers
15 views

How to treat missing values in a regression?

I have used the logarithmic form of wage as my independent variable in Stata. However, it contains missing values. Should I replace these with 0 or let them be?
0
votes
0answers
3 views

Comparing different models using LOOCV method [migrated]

I have to compare different models (OLS, BEST SUBSET, RIDGE, LASSO, PCR and PLS) using the LOO cross Validation (the criterion of comparison is the test-MSE). Could someone explain me how to do it ...
-1
votes
0answers
20 views

ridge regression in R

I used ridge regression on a data with multicollinearity ..but I was expecting that the standard error of each predictors would be smaller compared to the ols version.....but from the output inR,, I ...

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