Beantwortet
R code to matlab, or simply generating a zero mean gaussian and finding the covariance matrix
x=normrnd(0,1,5000,1); v=normrnd(0,0.3,5000,1); y=0.5*x+v; cov=mean(x.*y)-(mean(x)*mean(y)); cov s=cov*(sqrt(var(x)))*(sqrt...

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
Generating a histogram from lognormally distributed data
What about something like this: mu = 0.015; % mean particle size sg = 1.6; % standar...

etwa 5 Jahre vor | 1

Beantwortet
How to integral a pdf of a continuous random variable to calculate its entropy
Try this: pd = makedist('beta','a',50,'b',40); fun = @(x) pdf(pd,x) .* log( pdf(pd,x) ); H = -integral(fun,0,1)

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
Fit data to beta distribution
There is information here about how to fit a univariate distribution from an empirical CDFs with MATLAB. Unfortunately, it is a ...

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
how to create a pdf function of two variables that are in different uniform distribution
If they are independent then the joint pdf is the product of the marginal pdfs, so in this case pdf(x,y) = 0.01

etwa 5 Jahre vor | 0

Beantwortet
Calculate Exponetial Moving Covariance
Not really a hand, but maybe some hints...Let's say you have variables x and y, and you want the exponentially weighted rolling ...

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
Select sample from an array
Maybe this: ints = [2:7:259 3:7:259 4:7:259 5:7:259]; srtints = sort(ints); X1 = x(:,srtints);

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
Kruskal-Wallis test with very small p-values
p values can be anywhere between 0 and 1, depending on your data. a tiny p value like that is telling you that you would very r...

etwa 5 Jahre vor | 0

Beantwortet
Fitting a multivariate Gaussian distribution on a histogram
There isn't really a universal answer to "which distribution fits best", because there are an infinite number of different distr...

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
How to index through variable list in a table after doing calculation with each variable
myVars = {'Var1name' 'Var2name' 'Var3name'}; % list the names of the variables you want for iVar=1:numel(myVars) thisColu...

etwa 5 Jahre vor | 1

Beantwortet
How to obtain the standard error for each of the fitted parameters
The notion of a standard error assumes some kind of random sampling. For example, the standard error of your 'b' parameter refl...

etwa 5 Jahre vor | 0

Beantwortet
sqlite foreign key constraint not enforced
In case anyone else is interested, here is the answer from MATLAB technical support: This [is] a bug in executing PRAGMA querie...

etwa 5 Jahre vor | 0

Beantwortet
Weird fitting result from using 'ksdensity'
Try histogram(x,'Normalization','pdf')

etwa 5 Jahre vor | 1

| akzeptiert

Beantwortet
How to plot a spatial correlation with a p-value threshold?
After you get X (bottom of your first code segment): rCrit = 0.312; % Based on N=40 and alpha = 0.05, 2-tailed, from a table of...

etwa 5 Jahre vor | 0

| akzeptiert

Beantwortet
double truncated data sample
This is pretty ugly, but I think will do what you asked for: function [x]=generate_sample(n,eta,beta,theta,t1,t2) % ...

etwa 5 Jahre vor | 0

Frage

sqlite foreign key constraint not enforced
My question is how to get MATLAB's sqlite databases to enforce foreign key constraints. Here is a minimal working example illus...

etwa 5 Jahre vor | 1 Antwort | 0

1

Antwort

Beantwortet
How to use least square fit in MATLAB to find coefficients of my polynomial?
% It sounds like you have data arrays like these: nPoints = 100; H = rand(nPoints,1); C = rand(nPoints,5); % If so, comput...

etwa 5 Jahre vor | 1

| akzeptiert

Beantwortet
How to remove effect of "in" predictors on "out" predictors in stepwiseregression?
One way to think of it is that the "out" predictors will only improve the fit of the regression model if they bring in some new ...

etwa 5 Jahre vor | 1

Beantwortet
How to fit data in exponential fit (R = exp(-q*D)) and find coefficient "q" using Maximum Likelihood Estimate (MLE)?
As I read this question, it is about fitting a model rather than a distribution, so I don't think mle is appropriate. Instead, ...

etwa 5 Jahre vor | 0

Beantwortet
Multivariate analysis of variance in Matlab
You need to arrange your data in a table with one row per individual group member. For example, your first group seems to have ...

etwa 5 Jahre vor | 1

| akzeptiert

Beantwortet
Selecting a "random" element from an array with each element having it's own weighting
% Wts is your vector of weights. Wts = Wts / sum(Wts); % make sure they sum to 1 cumPrs = cumsum(Wts); % cumPr is the cumula...

etwa 5 Jahre vor | 0

Beantwortet
Help fitting data to an implicit equation
I would suggest using fminsearch. The error function to be minimized would be something like: function thiserr = err(x,y,t) ...

mehr als 5 Jahre vor | 0

| akzeptiert

Beantwortet
Chi-squared for multiple groups
The crosstab function will do this--it is not limited to 2x2 tables. Example: % Make up example data for 200 participants, codi...

mehr als 5 Jahre vor | 1

Beantwortet
using mle in matlab
One problem is that mle's search function (fminsearch) may try negative parameter values, in which case your pdf function return...

mehr als 5 Jahre vor | 0

Beantwortet
ttest2 with a group describing independent values (statistics)
No, it is not possible to use ttest2 as you suggest. Your design has 2 factors: gender and time (day/night) with repeated measu...

mehr als 5 Jahre vor | 1

| akzeptiert

Beantwortet
Generation of Conditional Random Variables
It sounds like the only "free" aspect of your new samples is the new total (say, 241 instead of 240). Once you have that new to...

mehr als 5 Jahre vor | 1

Beantwortet
Calculate Nakagami m parameter using the mle function
I think the minimum change you need is fast_fading=fast_fading(filtersize:end); fast_fading = fast_fading - min(fast_fading); ...

mehr als 5 Jahre vor | 0

Beantwortet
Mixed anova design function (unbalanced design)
If the goal of the analysis is to see if the two groups differ significantly in sleep pre-expt, then actually the simplest appro...

mehr als 5 Jahre vor | 0

Beantwortet
model parameter estimation from RMSE between modeled outputs and observations
Something like this. If it is too slow, note that you can use 'optimset' to pass fminsearch options that make it finish faster ...

mehr als 5 Jahre vor | 0

Beantwortet
model parameter estimation from RMSE between modeled outputs and observations
I assume the model is too complex for regression, etc. In that case, you might be able to do this with fminsearch, if there are...

mehr als 5 Jahre vor | 0