All Questions
1,569 questions with no upvoted or accepted answers
0
votes
0
answers
6k
views
Calculating average variance extracted (AVE) in AMOS discriminant validity
I was asked to calculate average variance extracted (AVE) to establish discriminant validity; I've ran CFA but ask how to calculate AVE following Fornell & Larcker’s (1981) test when having two ...
- 1
0
votes
0
answers
40
views
Variance of parameters
I have three estimated parameters, $\hat{\beta_0}$,$\hat{\beta_1}$ and $\hat{\beta_2}$, these follow the ordering $\hat{\beta_1}\leq\hat{\beta_0}\leq\hat{\beta_1}$, where these parameters are ...
- 839
0
votes
0
answers
30
views
Accounting for minimum dependent measure in data when fitting a distribution
I have what is possible a naive question. I am current comparing various models (i.e. distributions). And the comparisons do not involve different distributions but rather how the model is fed the ...
- 43
0
votes
0
answers
415
views
Effective variance for two independent variables
When you're fitting a model $y=f(x)$ to data (${x_i, y_i}$) with errorbars on both the independent ($x$) and response ($y$) variables, it's standard that you can define an 'effective variance' when ...
- 101
0
votes
0
answers
171
views
Create a simulation study using R to compare the accuracy (95% capture rate) and the lengths of the Chi-Squared confidence intervals
The minimum length confidence bounds for a normal population variance for chi-squared distribution is
Are they right?
GOAL: Create a simulation study using R to compare the accuracy (95% capture ...
- 207
0
votes
0
answers
52
views
comparing variation of a blended product from populations of different sizes (dilutions)
Original question: If population 1 consists of blended piles of size X_1 and population 2 consists of blended piles of size 4*X_1. Should I expect the standard deviation of X_1 to be equal to 4*the ...
- 131
0
votes
0
answers
237
views
can I compute the product of these two multivariate normal densities in a simple way
I have two multivariate normal densities and I parameterise them by the precision matrix (i.e. the inverse covariance matrix). One of them has a sparse precision matrix and the other one has a simple ...
- 4,730
0
votes
0
answers
163
views
Distance from bivariate Gaussian mean in terms of variance
Not sure if my question is a valid one but I will just put it out here.
Consider a bivariate data set $(x_i, y_i)$ $[i=1,...,n]$ to which a bivariate Gaussian Distribution is fitted. Now, consider ...
- 213
0
votes
0
answers
315
views
Obtaining sample variance from grouped data for goodness of fit test
This is a practice question I came across when dong some goodness of fit test examples.A company sells cloths by mail order.The size of clothes is defined by hip size; thus the height of customers of ...
- 1,273
0
votes
0
answers
341
views
Setting intercept to zero: Will this change both standard deviations and the error term?
After running a single regression with a forced zero intercept, I understand that $\beta$ (slope(s)) will change as $\alpha$ (intercept) will be set to zero. Easy.
$\rho = \beta(\sigma_x / \sigma_y)$ ...
- 101
0
votes
0
answers
261
views
How to test for variance between conditions
I have some Nanostring results that depict the fold change in expression after various conditions are applied. The people I am working with would like to know how to see what conditions give the ...
- 101
0
votes
0
answers
203
views
When can the variance be written as a function of expectation?
What kinds of distribution have variance as a function of expectation, i.e. let $X$ be a random variable of a distribution, $Var(X) = f(E(X))$ for some function $f$ ? Sufficient conditions including ...
- 19.8k
0
votes
0
answers
2k
views
Getting the MVUE of $\sigma^4$ for normal distribution
If x$_{1}$, x$_{2}$,...,x$_{n}$ ~ N($\theta$, $\sigma$$^{2}$), based on the fact that Y$_{1}$ = $\sum$(x$_{i}$) and Y$_{2}$ =$\sum$(x$_{i}$)$^{2}$ are complete and sufficient statistics, it can be ...
- 39
0
votes
1
answer
369
views
What is the variance of convolution of two random variables?
Consider two random variables $Z$ and $W$. Given the variances of $Z$ and $W$, how can we compute the variance of their convolution $Z \circledast W $?
As an example, please consider the case of noise ...
0
votes
1
answer
860
views
Is there any test to check variance stationarity in time series?
The question is straightforward: Is there any test to check variance stationarity (homoscedasticity) in time series?
And, if it exists, which are its implementations in R or Python?
- 11
0
votes
1
answer
146
views
Convergence of variance of sample median, pt. 2
Follow on question to this, answered negatively by Thomas Lumley. We reprint it here for convenience.
In this SE question, it is stated that there is a central limit theorem for the sample median, ...
- 128
-1
votes
1
answer
327
views
Unequal variance and sample size?
What is the effect of sample size on variance? If $n$ in two groups is different, does that automatically mean variance is not equal?
- 11
-1
votes
1
answer
35
views
Integration of exponential having ||Lx|| inside?
I am stuck with performing this integration. Can anyone help please?
$$
\mathbb{V}\mathrm{ar}[M_j] \stackrel{\text{def}}{=}
\mathbb{E}[M_j^2] =
e_j^T
\left(
\int_{\mathbb{R}^{n+1}} m^2 \pi^D_{\text{...
- 55
-1
votes
1
answer
1k
views
how to Normalize data(with noise) into 0-1 range good scale in mean and variance?
i have a matrix data. Perhaps some data in one cluster and another in some cluster.
data scale is between [0-1000](just example). and i want to normalize into [0-1] and good in mean and variance. it ...
