Statistics and Machine Learning Toolbox developer

Professional Interests: statistics, especially reliability/survival analysis, design of experiments, anova, simultaneous inference, visualization

Answered

Curve fitting: seversl curves to one

If you want nhh = a * (n1^b) * (n2^c) * (n3^d) consider taking logs log(nhh) = log(a) + b*log(n1) + c*log(n2) + d...

Curve fitting: seversl curves to one

If you want nhh = a * (n1^b) * (n2^c) * (n3^d) consider taking logs log(nhh) = log(a) + b*log(n1) + c*log(n2) + d...

1 month ago | 0

Answered

Do I purchase Statistics and Machine Learning Toolbox separately from MATLAB license?

There may be other options. If the GUI author can work with you, you may be able to replace use of tdfread by a newer core MATLA...

Do I purchase Statistics and Machine Learning Toolbox separately from MATLAB license?

There may be other options. If the GUI author can work with you, you may be able to replace use of tdfread by a newer core MATLA...

1 year ago | 0

Answered

Understanding the Stepwiselm PRemove

Daria, thanks for providing the data, allowing me to reproduce your results. It looks like the documentation is confusing or ...

Understanding the Stepwiselm PRemove

Daria, thanks for providing the data, allowing me to reproduce your results. It looks like the documentation is confusing or ...

1 year ago | 0

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Answered

How to obtain Std of Coefficients from Curve Fitting

You can get more information when you invoke the fit command: [obj,gof,opt] = fit(...) This gives the fitted obj, goodne...

How to obtain Std of Coefficients from Curve Fitting

You can get more information when you invoke the fit command: [obj,gof,opt] = fit(...) This gives the fitted obj, goodne...

2 years ago | 2

Answered

Nonlinear Regression with Errors in X and Y

If you just had y and one or more x variables as predictors, there is information about an errors-in-variables fit here: <htt...

Nonlinear Regression with Errors in X and Y

If you just had y and one or more x variables as predictors, there is information about an errors-in-variables fit here: <htt...

2 years ago | 0

Answered

Kernel Density estimation with chosen bandwidth, then normalize the density function (cdf) so that integral of cdf from min to max equal to 1 ; then take the first and second derivative of the cdf

You seem to want to do a number of things including integrating and specifying a bandwidth. Maybe this will get you started. ...

Kernel Density estimation with chosen bandwidth, then normalize the density function (cdf) so that integral of cdf from min to max equal to 1 ; then take the first and second derivative of the cdf

You seem to want to do a number of things including integrating and specifying a bandwidth. Maybe this will get you started. ...

2 years ago | 0

Answered

Unable to Generate Code out of Machine Learning Model

Your screen shot shows generating MATLAB code from the app. That code does training. I think you want to export a compact model ...

Unable to Generate Code out of Machine Learning Model

Your screen shot shows generating MATLAB code from the app. That code does training. I think you want to export a compact model ...

2 years ago | 0

Answered

How to perform stratified 10 fold cross validation for classification in MATLAB?

If you have the Statistics and Machine Learning Toolbox, consider the |cvpartition| function. It can define stratified samples.

How to perform stratified 10 fold cross validation for classification in MATLAB?

If you have the Statistics and Machine Learning Toolbox, consider the |cvpartition| function. It can define stratified samples.

3 years ago | 0

Answered

Conflicting results with multcompare when using the Kruskal-Wallis test on multiple groups

It's sad but true that there can be an overall difference according to one test, another test might not declare specific differe...

Conflicting results with multcompare when using the Kruskal-Wallis test on multiple groups

It's sad but true that there can be an overall difference according to one test, another test might not declare specific differe...

3 years ago | 0

Answered

Log likelihood for each distributions.

It's not clear to me what fails to match with what. These match: >> x = -5*log(rand(100,1)); >> pd = fitdist(x,'weibull'...

Log likelihood for each distributions.

It's not clear to me what fails to match with what. These match: >> x = -5*log(rand(100,1)); >> pd = fitdist(x,'weibull'...

3 years ago | 1

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Answered

bayesian logistic regression - slicesample - finding Machine learning parameters

It looks like you have the right idea. But I suspect the calculations are underflowing. You're multiplying thousands of probabil...

bayesian logistic regression - slicesample - finding Machine learning parameters

It looks like you have the right idea. But I suspect the calculations are underflowing. You're multiplying thousands of probabil...

4 years ago | 1

Answered

how to identify a fitglm output as being rank deficient from the resulting object

If your model is f, you could see if f.NumCoefficients > f.NumEstimatedCoefficients

how to identify a fitglm output as being rank deficient from the resulting object

If your model is f, you could see if f.NumCoefficients > f.NumEstimatedCoefficients

4 years ago | 0

Answered

How to calculate the correlation coefficient between an array and a matrix?

If you have the Statistics and Machine Learning Toolbox, it sounds like you want this: >> x = randn(20,3); >> y = x*[1 0...

How to calculate the correlation coefficient between an array and a matrix?

If you have the Statistics and Machine Learning Toolbox, it sounds like you want this: >> x = randn(20,3); >> y = x*[1 0...

4 years ago | 0

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Answered

Unable to access Stats toolbox functions

The toolbox has functions anova1, anova2, anovan, and rmanova among others. It does not have functions anova or ranova. Howev...

Unable to access Stats toolbox functions

The toolbox has functions anova1, anova2, anovan, and rmanova among others. It does not have functions anova or ranova. Howev...

4 years ago | 1

Answered

plotSlice - what are the numbers below the plots?

The prediction shown at the left of the plot is the value given by the model when the predictors are set to the numbers shown be...

plotSlice - what are the numbers below the plots?

The prediction shown at the left of the plot is the value given by the model when the predictors are set to the numbers shown be...

4 years ago | 3

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Answered

Does stepwisefit function is able to evaluate using adjusted R-squared instead p-value?

There is a newer function that can do that: load hald stepwiselm(ingredients,heat,'Criterion','adjrsquared')

Does stepwisefit function is able to evaluate using adjusted R-squared instead p-value?

There is a newer function that can do that: load hald stepwiselm(ingredients,heat,'Criterion','adjrsquared')

4 years ago | 1

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Answered

Why is fitlm (or regess) and estimation using mathematical equations giving different results?

The first two columns of coefficients have what appear to be exact zeros in row 13, corresponding to column 12 of X because of t...

Why is fitlm (or regess) and estimation using mathematical equations giving different results?

The first two columns of coefficients have what appear to be exact zeros in row 13, corresponding to column 12 of X because of t...

4 years ago | 0

Answered

What is the difference between the regress function and the fitlm function

Take a look at the 12th and 13th columns of X. It looks to me like the 12th may be constant or may differ by a constant from the...

What is the difference between the regress function and the fitlm function

Take a look at the 12th and 13th columns of X. It looks to me like the 12th may be constant or may differ by a constant from the...

4 years ago | 0

Answered

Decision trees, only binary branches?

If you fit a classification tree to the famous Fisher iris data, you get this: >> load fisheriris >> f = fitctree(meas,s...

Decision trees, only binary branches?

If you fit a classification tree to the famous Fisher iris data, you get this: >> load fisheriris >> f = fitctree(meas,s...

4 years ago | 0

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Answered

How can I make DOE design?

Here are two ways to do it. First, specify that you have 5 factors a-e and you want a resolution 5 design. Resolution 5 means yo...

How can I make DOE design?

Here are two ways to do it. First, specify that you have 5 factors a-e and you want a resolution 5 design. Resolution 5 means yo...

4 years ago | 1

Answered

Separate Drawing of Gaussian Mixture Model

You did something like this: x = [randn(4000,1)/2; 5+2*randn(6000,1)]; f = fitgmdist(x,2); histogram(x,'Normalization...

Separate Drawing of Gaussian Mixture Model

You did something like this: x = [randn(4000,1)/2; 5+2*randn(6000,1)]; f = fitgmdist(x,2); histogram(x,'Normalization...

4 years ago | 2

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Answered

clustering, matlab, nominal data

For hierarchical clustering, consider using Hamming distance. Here's an example that isn't realistic but that illustrates what t...

clustering, matlab, nominal data

For hierarchical clustering, consider using Hamming distance. Here's an example that isn't realistic but that illustrates what t...

4 years ago | 0

Answered

Why confidence interval distributions overlap the distribution?

A couple of things. First, take out your truncate statements and run the code. You'll see that the "LB" cdf is substantially bel...

Why confidence interval distributions overlap the distribution?

A couple of things. First, take out your truncate statements and run the code. You'll see that the "LB" cdf is substantially bel...

4 years ago | 0

Answered

fitnlm w/ table using not all Variables

You can specify modelfun using variable names: load carsmall t = table(MPG,Weight,Origin) nlm = fitnlm(t,'MPG~b1+b2*W...

fitnlm w/ table using not all Variables

You can specify modelfun using variable names: load carsmall t = table(MPG,Weight,Origin) nlm = fitnlm(t,'MPG~b1+b2*W...

4 years ago | 0

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Answered

Dimensions Reduction in Matlab using PCA

The first component explains most of the variation in the columns of DATA, but Y is not involved in that. Of course I don't unde...

Dimensions Reduction in Matlab using PCA

The first component explains most of the variation in the columns of DATA, but Y is not involved in that. Of course I don't unde...

4 years ago | 1

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Answered

PDF (Probability Density Function) of a 2D matrix of values

If you have your data in the matrix M and you want to ignore the zeros and the relative locations of the values, you could try ...

PDF (Probability Density Function) of a 2D matrix of values

If you have your data in the matrix M and you want to ignore the zeros and the relative locations of the values, you could try ...

4 years ago | 0

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Answered

How to fit a general-linear mixed-effects model with categorical variables?

Try data_nr_acquisitions.problem_type = categorical(data_nr_acquisitions.problem_type) before you do the fit.

How to fit a general-linear mixed-effects model with categorical variables?

Try data_nr_acquisitions.problem_type = categorical(data_nr_acquisitions.problem_type) before you do the fit.

4 years ago | 0

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Answered

What is exactly the kmeans ++ algorithm? How do you actually go about implementing it?

First off, if you look inside kmeans.m you should find an implementation of this. I'm hoping this is the kind of information ...

What is exactly the kmeans ++ algorithm? How do you actually go about implementing it?

First off, if you look inside kmeans.m you should find an implementation of this. I'm hoping this is the kind of information ...

4 years ago | 0

Answered

What is "Adjusted Resonse"

The adjusted response function isn't a diagnostic plot like an added variable plot, where you try to investigate or isolate the ...

What is "Adjusted Resonse"

The adjusted response function isn't a diagnostic plot like an added variable plot, where you try to investigate or isolate the ...

4 years ago | 0

Answered

Using every level of a categorical array in a regression

You could try using the DUMMYVAR function to generate indicator variables for each of your categories, then omit the constant te...

Using every level of a categorical array in a regression

You could try using the DUMMYVAR function to generate indicator variables for each of your categories, then omit the constant te...

4 years ago | 0