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how to select random rows from a matrix?
Statistics Toolbox includes a nice function called randsample % Generate a matrix named foo foo = randn(10000,2); ...

presque 13 ans il y a | 4

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Linear data fitting
From my perspective, the easiest way to solve this one is # Fit a linear model to the complete data set # Apply a clustering al...

presque 13 ans il y a | 0

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Which curve fitting function do I need?
nlinfit uses optimization solvers under the hood, so it's not too surprising that you're getting the same answer. nlinfit is pa...

presque 13 ans il y a | 1

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General Least Squares Fit
Thanks for clarifying. From the sounds of things, you need some kind of solution for non-parametric fitting. The choice of...

environ 13 ans il y a | 0

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General Least Squares Fit
I am somewhat confused by the question. Regression analysis is used to estimate a set of regression coefficients than minimiz...

environ 13 ans il y a | 0

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Multinomial logistic regression
The following example deals with Poisson regression rather than logistic regression. I'm posting this because it includes a fair...

environ 13 ans il y a | 0

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How to estimate Standard Error for the coefficients in ridge regression aproach
If you're working with a ridge regression model (as opposed to lasso or elastic net) then its relatively easy to code up a paire...

environ 13 ans il y a | 1

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Populating a 3D lookup table
Hi Stephen I did a webinar a couple years back focusing on using sftool to generate lookup tables for Simulink. The webi...

environ 13 ans il y a | 0

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Markov Chain - Hidden Markov Model; how to create markov chains and combine them to a hidden markov model
When I am working with Markov Chains I'm normally looking at stationary distributions which, by definition, don't depend on the ...

environ 13 ans il y a | 1

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Bootstrap sampling depending on portfolio
Hi Philip I attached a couple different examples of residual bootstraps using MATLAB The following reference provides some...

plus de 13 ans il y a | 0

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Curve fitting to data sets with multiple parameters
The easiest way to solve this type of problem is the nlinfit function inside Statistics Toolbox. Here's a simple example that d...

plus de 13 ans il y a | 1

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Optimal(default) bandwidth estimation method
You can open ksdensity.m in your editor and inspect the bandwidth estimation code. This section of the code starts at line 29...

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Bootstrap for surface fit goodness of fit stats
Few quick observations First: There are a lot of different ways to bootstrap a regression model. Some of the more common exam...

plus de 13 ans il y a | 1

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Multi-Dimensional Data for SVM
Hi Ziggy First: Statistics Toolbox has a number of good classification algorithms. The 11a release includes a variety of di...

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how to use cfit to get fitobject and gof from a separately provided line
The aren't any constructor options for the Fit Objects in Curve Fitting Toolbox. The easiest way to accomplish your goal is t...

plus de 13 ans il y a | 0

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Interpolating Multivariate time series
Handling missing data is a very complicated topic. There are a number of different approaches that you can use including listwi...

plus de 13 ans il y a | 0

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Problem of robust fitting using the "robustfit" function
Hi Massinissa In your first example, you are fitting Z as a function of X and Y. In the second you are fitting X as a function...

plus de 13 ans il y a | 0

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bhhh method for nonlinear regression
BHHH is a specific optimization algorithm. Under certain conditions, the BHHH algorithms is guaranteed to converge. I am not...

plus de 13 ans il y a | 0

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Need Help in Monte Carlo and comparing operational sequence

plus de 13 ans il y a | 0

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Multi level regression analysis
Statistics Toolbox includes two different algorithms (nlmefit and nlmefitsa) for fitting nonlinear mixed effects model. nlmefit...

plus de 13 ans il y a | 1

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Appending dataset of varying length
Hi Oleg This strikes me as more of a data representation issue than a question of MATLAB syntax. Your eventual solution will...

plus de 13 ans il y a | 0

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Bioinformatics GO Ontology, leave-one-out cross validation
Here's a simple example that shows how to do leave one out cross validation using the cvpartition and crossval commands in Stati...

plus de 13 ans il y a | 0

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Residuals from Regress
% Generate some random data X = linspace(1,100,100)'; Y = X + randn(100,1); % Use Curve Fitting Toolbox to genera...

plus de 13 ans il y a | 0

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Nonlinear fit to multiple data sets with shared parameters
Hi Kenneth Coincidentially, I did a webinar a couple weeks back that uses lsqcurvefit to solve just this type of problem. You ...

plus de 13 ans il y a | 0

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removing outliers
Automatically detecting outliers is tricky stuff. You normally need fairly precise information regarding your data as well as t...

plus de 13 ans il y a | 4

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Fitting data from differential scanning calorimetry to the Lumry-Eryring equation
Much as I love Curve Fitting Toolbox, I think that this is a case where Optimization Tbx will suffice....

plus de 13 ans il y a | 0

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Fitting data from differential scanning calorimetry to the Lumry-Eryring equation
Hi William I did a quick Internet search on "Lumry-Eyring". I found a lot of references to kinetic models. While the curves ...

plus de 13 ans il y a | 0

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Ridge regression and MSE
Use the "scaled" option to restore the coefficient estimates to the scale of the original data. You can then use b to estimat...

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nonlinear regression
The quality of a nonlinear regression is often highly dependent on the starting conditions that you provide to the optimization ...

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Curve fitting to experimental sets of data
1. Start by using the Curve Fitting Tool to fit one of your data sets. 2. Select "Generate Code" from the file menu. This ...

plus de 13 ans il y a | 1