search for: homoskedasticity

...ta: reg GQ = 1.7092, df1 = 327, df2 = 327, p-value = 7.93e-07 studentized Breusch-Pagan test data: reg BP = 15.8291, df = 23, p-value = 0.92 Breusch-Pagan test data: reg BP = 377.5604, df = 23, p-value < 2.8e-18 bptest and gq.test sport pretty straight forward examples saying the H0 = homoskedasticity. The ncv.test clarifies the same in its description. Thus the studentized bptest appears to be the only one to support my first intuition from the graphical solution. I am really disturbed what to do know and how to interpret my results... Can someone lead the way ? thx in advance matt

...ts ML estimator, which I see have just been developed in an R package called “sampleSelection.” But in that case, I have I would guess in my ignorance that I’m way biased because it assumes specific error distributions and that they are homoskedastic. (I could transform the data in advance to get homoskedasticity if necessary). I could make an instrument for probability(y*>0) and multiply that by each observation of permits, avoiding distributional assumptions in e (but not in prob(y*>0)), but would that give me really high variance? (And is there an easier way to find variance than algebraically fi...

i a have transformed my data to data frame named df with only column names(no rownames).each column represnt one sample with 3 observations (in deed nrow(df)=3, and ncol(df)=92).in order to check homoskedasticity of variance of my 92 samples i do: bartlett.test(df) it work and give me a result.but i'm afread of getting false result,knowen that a call of such function require a vector of data x and a factor g . g is omitted when x is a list of vector. is the call that i do true? is a data frame in my...

I am conducting an experiment with four independent variables each of which has three or more factor levels. The sample size is quite large i.e. several thousand. The dependent variable data does not pass a normality test but "visually" looks close to normal so is there a way to compute the affect this would have on the p-value for ANOVA or is there a way to perform an nonparametric test

Dear colleagues: I've been storing up this question for a long time and apologize for the length and verbosity of it. I am having trouble in consulting with graduate students on their research projects. They are using surveys to investigate the sources of voter behavior or attitudes. They have predictors that are factors, some ordered, but I am never confident in telling them what

Dear all, I am conducting a full factorial analysis. I have one factor consisting in algorithms, which I consider my treatments, and another factor made of the problems I want to solve. For each problem I obtain a response variable which is stochastic. I replicate the measure of this response value 10 times. When I apply ANOVA the assumptions do not hold, hence I must rely on non parametric

Hi all, Is it possible to have a test value for assessing the normality of residuals from a linear regression model, instead of simply relying on qqplots? I've tried to use fitdistr to try and fit the residuals with a normal distribution, but fitdsitr only returns the parameters of the distribution and the standard errors, not the p-value. Am I missing something? Cheers, Federico