All Questions

0
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0answers
2 views

Determinant of the covariance matrix in a normal distribution

Suppose a $p \times 1$ vector $x \sim N_p(\boldsymbol 0, \boldsymbol \Sigma_1)$. Now, There is another covariance matrix $\boldsymbol \Sigma_2$. We know that $|\boldsymbol \Sigma_2| < |\boldsymbol ...
0
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0answers
8 views

Statistical analysis of variable data

I have the statistical research data. I have 6 treatments with 3 boxes for each treatment. I am raining on the treatments every week and collecting data. The data is variable within boxes and also ...
0
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0answers
5 views

modeling a proportion with seasonality removed

I have a time series of proportions that typically fall in the 0.01-0.05 range. I had intended to use GLM to model these proportions, but I ran into trouble when I needed to first remove a strong ...
0
votes
1answer
16 views

Log transformation for data?

If the data is between (0,1) because of some kind of vector normalization to get rid of background noise, is it still OK to do log transformation to improve normality? Or we have to do logit ...
0
votes
0answers
4 views

How to plot the US maps with selected locations (longitude and latitude of the locations are known)? [migrated]

I've been struggling with the following R plotting of the US map and wonder if any of you have suggestions on how the plot should be done. Here is what I have tried: ...
0
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0answers
3 views

Variance of precision in conjugate prior

How can I calculate the variance of the precision in a normal distribution, knowing I used a conjugate prior?
0
votes
1answer
6 views

Problem displaying st. errors after lincom using outreg2

I am running two regressions in Stata: one without controls and another with controls. I'm using lincom to find the coefficient and se for the sum of two of my regressors. I am then using outreg2 to ...
0
votes
0answers
7 views

Maximizing likelihood versus MCMC sampling: Comparing Parameters and Deviance

I am working in R. I use lm() for maximizing the likelihood in the first analysis, and STAN to sample from the posterior in a second analysis. ...
1
vote
0answers
10 views

Using Factor Analysis prior to repeated measures ANOVA

Please note, stats is NOT my area (hence why I need help!) and I may not be using the correct terminology. I hope I can explain my question clearly enough. BACKGROUND: I have collected behavioural ...
1
vote
0answers
9 views

Interpreting output from cvFit(), understanding cross-validation in classification tree model

I am trying to understand how to interpret the output for cvFit(). The data is from UCI's ML repository. This is my model ...
0
votes
0answers
29 views

What is the distribution of the conditional mean E(Y|X) in a multiple regression?

Suppose the model is $$ Y = b_0 + b_1X_1 + b_2X_2 + b_3D + b_4X_1D + e \\ e \sim\mathcal N(0, \sigma^2) $$ Where $D$ is a categorical variable. $$ E(Y|X_1, X_2, D=1) \sim\mathcal ?? \\ E(Y|X_1, ...
0
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0answers
4 views

Inhomogeneous exponential distribution?

I don't know exactly what I am looking for but here are my current thoughts : I have a sequence of arrival time $t_1,\dots,t_n$ and the rate $\lambda(t)$ at which these events occurs varies through ...
0
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0answers
8 views

Y axes on the logit scale and centered in gbm.plot [migrated]

I am currently exploring the gbm functions in the package dismo to create boosted regression trees for species distribution modeling. I have been using the dismo vignettes as well as the 2008 paper "A ...
0
votes
1answer
7 views

Temporal linkage between two lists of data

I have 2 lists, representing a time series: list_a = [23,43,29,45,6,12,240] list_b = [13,23,11,35,60,52,40] i.e. list_a[0] is value in first year....list_a[6] is ...
0
votes
0answers
9 views

Determining the “dominant” color in an image with R [migrated]

I am hoping this is the right place for this question. I want to know if with R, its possible to sample images, and determine their dominant color? If so, could you point me towards a package?
0
votes
0answers
2 views

Conditional Distribution of an Independent Variable in a Spatial Durbin Model

Let $X=[X_1 X_2 X_3 ... X_p] $be a matrix of p independent variables where $X_i=[x_{i1} ... x_{in}]'$ is a nx1 vector. Let W be a nxn weight matrix based upon queen contiguity (so zero's along the ...
0
votes
0answers
10 views

Unable to formulate MLE for minimum distance estimator

The model generating the observation is of the form $y_n = A^Tx_n + U_n$ where $x$ is the output of a a linear stationary model and $U$ is a zero mean Gaussian noise of known variance. The set of ...
1
vote
1answer
17 views

Time Series Function - Constant vs Piecewise

I have daily data for online marketing $ spend and the number of clicks to the website gained. I want to determine a function that 'maps' the two together. I cannot use normal linear regression ...
0
votes
1answer
24 views

Why can't we add all the individual Pearson's $r$'s in a multiple regression and calculate $R^2$ based on this sum?

Why can't we add all the individual Pearson's $r$'s in a multiple regression and calculate $R^2$ based on this sum? Is there an easy mathematical explanation to this as $r^2$ is squared and don't add ...
0
votes
1answer
24 views

What is the relation between multiple-regression and pearson's r?

What is the relation between these two, not $r^2$, but Pearson's $r$ and multiple $r$?
0
votes
0answers
12 views

Expand scale bias correction factor (infinite series) [duplicate]

I am trying to expand a scale bias correction factor to 10 to 15 terms but I am spinning my wheels. Too long since engineering school. Here is the series. I have values for $m$ and $T$. ...
0
votes
1answer
10 views

Probabilistic comparison of two mixture models?

Given two gaussian mixture models (GMMs) with different degrees of freedom, is there a way to determine the probability that one is generated from the other? That is, can we give a probability to the ...
5
votes
2answers
83 views

Why is GLM different than an LM with transformed variable

As explained in this course handout (page 1), a linear model can be written in the form: $$ y = \beta_1 x_{1} + \cdots + \beta_p x_{2} + \varepsilon_i$$ , where $y$ is the response variable and ...
1
vote
0answers
20 views

p-value over q-value?

I am trying to figure out when (during multiple testing) to use $p$-values and when to use $q$-values. This student thesis explains how this particular theorem (Eq. 11 in the paper) allows one to ...
0
votes
2answers
22 views

Does Support Vector Machine handle imbalanced Dataset?

Does SVM handles imbalanced dataset? Is that any parameters (like C, or misclassification cost) handling the imbalanced dataset?
2
votes
2answers
34 views

Does the central limit theorem apply to these probability density functions?

Let's say you have n uniform random variables from 0 to 1. The distribution of the average of these variables approaches normal with increasing n according to the central limit theorem. What if ...
0
votes
0answers
20 views

confidence intervals and type II errors

I am using confidence intervals to test whether a parameter includes a certain value, 1. The sample size is reasonably large. Let us say my parameter estimate is 1.1 (95% CI: 0.99,1.2). So I cannot ...
0
votes
1answer
14 views

meaning of normalized mutual information

I read a paper which shows the value of normalized mutual information for two random variables is around 0.1 to 0.2 and it says so these two variables are statistical significantly correlated. I don't ...
0
votes
0answers
16 views

Fundamental Issues with Influence weighted resampling for bootstrapped predictions

I have a large database 1mill+ from which it is known that there are many influential points and outliers. I am interested in generating a series of predictions from subsets (1,000+) of the data and ...
0
votes
0answers
4 views

how to do post hoc comparison between groups in LGM by amos

I have three time point data and I using LGM by amos. I want to do group comparison with LGM anybody can help me. I am doing an intervention study in that I have pre, post and follow-up data.I want to ...
0
votes
0answers
18 views

difference between machine learning and stastitical technique [duplicate]

Is there any difference between machine learning and stastitical techniques. I have searched a lot some researchers say that there are some overlap some are saying there is no difference.Can you give ...
0
votes
0answers
9 views

Cox proportional hazards (setting a reference level and an interaction with time)

I am currently trying to analysis some data in R using Cox proportional hazards. I have been able to get my coxph model to run but, I am having some coding difficulties. I have two factors (individual ...
0
votes
2answers
16 views

Accepted Method for Selecting a Validation Set in Python

Is there an accepted method for separating out a validation set in python? In R I would use the sample function. I have 4000 training instances as json and I want ...
0
votes
1answer
13 views

Discrepancy between Kaplan-Meier curves and Cox Model

I have plotted Kaplan-Meier curves of survival times for cancer patients with above and below average levels of Copy Number Variation (CNV), and performed a log-rank test for each cancer type. I have ...
2
votes
1answer
22 views

Probit or Logit in Generalized Linear Model [duplicate]

I'm trying to apply GLMs on a dataset in which dependent variable Y is dichotomous. I applied either logit and probit models, and probit fitted better than logit model. How do I justify the choice of ...
1
vote
0answers
17 views

Fit a VAR model with R

I have a bivariate time series z_t where z_1t is the change in monthly US treasury bills (maturity 3 months) and z_2t the inflation rate,in percentage, of the U.S. monthly consumer price index ...
2
votes
0answers
14 views

Mean and variance of Cox process

Consider the (doubly-stochastic) Poisson point process with rate $ \lambda(t) = \rho e^{-t/\tau} $ where $\rho\sim\Gamma(\alpha,\beta)$ is a Gamma-distributed random variable. I require the mean ...
0
votes
0answers
22 views

Obtain factor scores in data set with missing values

I would like to obtain factor scores after factor analyzing data that contain missing values. I'm using Stata 13 to run the analysis. Here is the basic code (borrowed from the UCLA site): ...
-1
votes
0answers
13 views

Cran Package from Google for Forecasting multivariate time series [on hold]

Recently, i saw the package that can forecasting multivariate time series and evaluate the effects of variables like promotion at main time series. Please help me to find it again
1
vote
0answers
12 views

How to use delta method for standard errors of marginal effects?

I am interested in better understanding the delta method for approximating the standard errors of the average marginal effects of a regression model that includes an interaction term. I've looked at ...
0
votes
0answers
4 views

Naive ElasticNet in the glmnet package

In the R package glmnet, does it calculate the Naive form of ElasticNet or is the output rescaled with the term (1 + lambda)?
1
vote
0answers
22 views

Calculate 1D Random Walk Expected Iterations to return to origin

I'm trying to solve a stats problem as outlined below; I'm a bit new, however, and I'm not sure how I could solve this problem. Assume someone has lost their keys, and uses an inefficient random walk ...
6
votes
1answer
49 views

Unified view on shrinkage: what is the relation (if any) between Stein's paradox, ridge regression, and random effects in mixed models?

Consider the following three phenomena. Stein's paradox: given some data from multivariate normal distribution in $\mathbb R^n, \: n\ge 3$, sample mean is not a very good estimator of the true mean. ...
4
votes
0answers
15 views

Relationship between Gini Importance and Prediction Performance (say AUC)?

I want to use the decrease in Gini impurity to rank features for my random forest classifier. I understand that the decrease in Gini impurity at one node is calculated as: $$ \Delta i(n) = i(n) - ...
1
vote
0answers
8 views

Assessing predictor contribution to model output

Many of machine learning methods are considered as "black boxes". Examples of such methods are SVM, Neural Networks, Random forests etc. One may apply sensitivity analysis techniques (as described for ...
1
vote
0answers
21 views

How to determine if GLM quadratic term should be set up orthogonal or non-orthogonal

I am setting up a GLM in R where I have only one predictor variable and its quadratic form. I understand that in R I have 2 options. ...
1
vote
1answer
49 views

How can I remove multicollinearity from my logistic regression model?

I am working on Sales data. i have binary variable win/loss the opportunities and rest are the activities done by sales force (sales guys) with 40+ variables (different types of activities done for ...
0
votes
0answers
22 views

Generating two normally joint distributed Random Variables

If I generated two random variables with mean $\mu_1$ and $\mu_2$, but use the covariance matrix as the second parameter of the normal distribution - does this imply that the two variables are jointly ...
0
votes
0answers
7 views

Slope loading in LGM by AMOS

I have three time point data of my intervention study(pre-test, post-test and follow-up test,0, 2.5 month and 3.5 month from initial data). I am confused with slope loading how to load this value. I ...

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