Questions tagged [nonparametric]
Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters.
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Test if multidimensional distributions are the same
Lets say I have two or more sample populations of n-dimensional continuous-valued vectors. Is there a nonparametric way to test if these samples are from the same distribution? If so, is there a ...
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Is there an optimal bandwidth for a kernel density estimator of derivatives?
I need to estimate the density function based on a set of observations using the kernel density estimator. Based on the same set of observations, I also need to estimate the first and second ...
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How to correctly apply the Nemenyi post-hoc test after the Friedman test
I'm comparing the performance of multiple algorithms on multiple data sets. Since those performance measurements are not guaranteed to be normally distributed, I chose the Friedman Test with the ...
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Non-parametric test equivalent to mixed ANOVA?
I have an experiment with two groups under different conditions where a single dependent variable is measured repeatedly at multiple times. It seems the right parametric test to use here is two-...
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Density estimation for large dataset
I have a unidimensional data set with more than 1000000 observations.
Assuming that those observations are independent realizations of the same random variable I need to estimate the underling ...
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Non-parametric for two-way ANOVA (3x3)
My dependent variable is continuous, non-normal (skewed left according to Shapiro-Wilk test). I have two independent variables (treatment group by colour, food type). There are 3 levels within each ...
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"One-tailed" Levene Test
F-tests can be two-tailed (to test that $s_1^2 \ne s_2^2$) or one-tailed (to test that $s_1^2 > s_2^2$).
How can I modify Levene/Brown-Forsythe to be "one-tailed", that is, to test $s_1^2 > s_2^...
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Kruskal-Wallis test data considerations
I'm about to apply Kruskal-Wallis test (non-parametric ANOVA) on three groups of unequal length. I was taught/advised to apply Krukal-Wallis only if:
dependent variable is at least at ordinal level ...
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Two broad categories of dimensionality reduction: with and without an explicit mapping function
I think there are two very broad categories of dimensionality reduction (DR) techniques:
We can compute an analytic form of mapping from the training data, say $x\mapsto y: y=f(x)$, where $f(\cdot)$ ...
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Correlation between vegetation and erosion
I am wanting to find the correlation between two variables: a categorical vegetation variable (with categories 1-4) and a continuous variable of erosion (with values anywhere between 0.2 and 9). I ...
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Can we ALWAYS assume normal distribution if n >30?
I'm in a debate with a coworker and I'm starting to wonder if I'm wrong but the internet is confusing me more.
We have continuous data $[0, \infty)$ that is retrospectively selected on individuals. ...
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Wilcoxon Test - non normality, non equal variances, sample size not the same
I know there are already a lot of posts out there, but I couldn't find this exact combination in any of them.
Comparing two samples (Prices associated with men and with women), but I have neither the ...
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Local polynomial regression: Why does the variance increase monotonically in the degree?
How can I show that the variance of local polynomial regression is
increasing with the degree of the polynomial (Exercise 6.3 in Elements
of Statistical Learning, second edition)?
This question has ...
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Prove the relationship between Walsh averages and Wilcoxon signed rank test
In my lecture notes it is stated that
sum of all positive signed ranks (defined in Wilcoxon signed rank test) = the number of Walsh averages that are greater than median
How can I prove this ...
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What is a statistical significance test for two Poisson distributions?
Say that I have two Poisson distributions. These were modelling after count data.
How would I determine statistical significance between these two distributions? That is, how would I determine ...
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