FAQ Database Discussion Community

Loop through various data subsets in lm() in R

r,loops,regression,subset

Change basic assumptions of “add trendline” in excel

excel,regression,trendline
I'm plotting some interaction effects that stem from a regression in stata. I'm using excel for convenience. The data are curvilinear and I'm adding a polynomial trendline to maximize the fit. The problem I have is that the trendline function seems to assume that the x values are 1, 2,...

How to find algo type(regression,classification) in Caret in R for all algos at once?

r,machine-learning,classification,regression,caret

Placing Limits on Optim

r,optimization,regression,rscript
i'm trying to use an algorithm to minimise the least squares of models. I'd like to be able to confine all the parameters to within sensible ranges however when i run this script for whatever reason it is disregarding my limits. More of a debugging issue than anything else. Any...

Constrained high order polynomial regression

matlab,regression
I am doing some bone segmentation whereas the result of this segmentation is points placed in a circular pattern around this bone. However as it is taken using a qCT scan, there is quite a lot noise (from e.g. flesh) on the points that i have. So the overall problem...

Plotting a independent variable under a parameter of another variable in R

r,plot,regression
I have a function predictshrine<-0*rain-399.8993+5*crops+50.4296*log(citysize)+ 4.5071*wonders*chief+.02301*children*deaths+1.806*children+ .10799*deaths-2.0755*wonders-.0878*children^2+.001062*children^3- .000004288*children^4-.009*deaths^2+.0000530238*deaths^3+ 7.974*sqrt(children)+.026937*wonders^2-.0001305*wonders^3 I also have a sequence children<-seq(0,100,length=500) And a for loop for(deaths in c(0,5,10,50,100,200)) Now what i want to do is be able to plot predictshrine vs children when deaths equals certain amounts and...

Getting statsmodels to use heteroskedasticity corrected standard errors in coefficient t-tests

python,regression,statsmodels
I've been digging into the API of statsmodels.regression.linear_model.RegressionResults and have found how to retrieve different flavors of heteroskedasticity corrected standard errors (via properties like HC0_se, etc.) However, I can't quite figure out how to get the t-tests on the coefficients to use these corrected standard errors. Is there a way...

Modelling interactions with only a subset of the levels of a factor in R

regression,interaction
Let's first look at lm. I have a continuous explanatory $X$ and a factor $F$ modelling seasonal aspects (in the example 8 levels). Let $\beta$ denote the slope for $X$ then I want to model interactions of the slope with the factor. It is some kind of physical model thus...

An error while looping a linear regression

r,loops,data.frame,regression
I would like to run a loop that will run per each category of one of the variables and produce a prediction per each regression so that the sum of the prediction variable will be deduced from the target variable .Here Is my toy data and code: df <- read.table(text...

forward subset selection in R without intercept

r,statistics,regression,regression-testing
Hey so I am developing a multiple regression model and using the forward subset selection method to reduce the number of parameters and using "mallows Cp" as a selection criterion. However this is an engineering problem and it does not make sense to have an intercept,, i.e. when all the...

Multiple regressions with subsets of data using dplyr in R

r,regression,dplyr

Input format for functions in package strucchange?

r,regression,trend
I'm trying to do change point detection with ´monitor´ from the strucchange package, but I have trouble getting a useful output. My input is a time stamped dataframe, and I would like the breaks to be returned as dates, but they are returned as observation number: cDF1 <- myDF[1:80,] >...

Nonlinear total least squares/Deming regression

r,regression
I've been using nls() to fit a custom model to my data, but I don't like how the model is fitting and I would like to use an approach that minimizes residuals in both x and y axes. I've done a lot of searching, and have found solutions for fitting...

chaid regression tree to table conversion in r

r,packages,regression,decision-tree
I used the CHAID package from this link ..It gives me a chaid object which can be plotted..I want a decision table with each decision rule in a column instead of a decision tree. .But i dont understand how to access nodes and paths in this chaid object..Kindly help me.....

R: HAC by NeweyWest using dynlm

r,time-series,regression