10
votes
0answers
137 views

Behaviour of prediction bands

Let's generate some noisy data with uneven noise. ...
2
votes
1answer
72 views

How to get confidence bands of parameters from a fitting procedure?

I have done fitting of data points with a given model that has two parameters (A and B), using NonlinearModelFit. The result of the fit is the maximum of the ...
4
votes
1answer
138 views

Multinomial logistic regression

Has anyone done multinomial logistic regression in Mathematica? The binomial case is essentially done on the LogitModelFit documentation page and works fine. I am ...
6
votes
1answer
137 views

Obtaining standardised regression coeffiecients

Regression coefficients are the constant that indicate the rate of change in one variable as a function of change in another. Standardised regression coefficients are the same, but refer to a change ...
6
votes
1answer
193 views

Fix end point in smooth kernel distribution density

I am using some extreme value fitting method which results in a parametric distribution for values exceeding some threshold, all values $\geq 0$. For smaller values I'd like to use a smooth kernel ...
3
votes
1answer
144 views

Getting slightly different results in fitting a logit model in R and Mathematica

I'm fitting some data to a Logit model in both Mathematica and R and I'm getting slightly different results. R code: ...
3
votes
0answers
154 views

Mathematica Complains about Non Symmetric Covariance matrix, when it's not the case

I was doing some fitting with Mathematica7 using NonlinearModelFit. It's quite long the program to do the fit and that's why I am not displaying here ... It goes ok, and I can get the fit parameters ...
13
votes
5answers
2k views

Estimate error on slope of linear regression given data with associated uncertainty

Given a set of data, is it possible to create a linear regression which has a slope error that takes into account the uncertainty of the data? This is for a high school class, and so the normal ...
2
votes
2answers
221 views

Non-linear trend reduction with missing data

How can I reduce a non-linear trend of some data series if there are parts of "no data", represented by the value 99999? For example: ...
24
votes
4answers
2k views

Simultaneously fitting multiple datasets

What is the proposed approach if one wants to simultaneously fit multiple functions to multiple datasets with shared parameters? As an example consider the following case: We have to measurements of ...