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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Is bootstrapping inherently Frequentist? If so, how do we do a Bayesian non-parametric two-sample test?
I normally use frequentist statistics but I now want to use Bayesian statistics as I want to carry out a two-sample (randomised control trial) test that includes prior information. I have an existing ...
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Appropriate Trend Analysis Test for Small Sample Size
Note: I have read Finding an appropriate trend test but unfortunately this post does not apply for me
Suppose I have a small sample of data for 2 numeric variables $T$ and $Y$ where $T$ represents ...
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I want to show by simulation that the Wilcoxon test is more robust than the Student test for non-normally distributed data
I want to test by simulation that the Wilcoxon test is more robust than the Student test for non-normally distributed data.
For example, I'm testing the ...
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Welch ANOVA for Comparisons of Elevation & altered Sediment Accretion of Sea Ecosystems: Large DEM with no normal distribution & heterogeneity
I am investigating the elevation characteristics and sediment accretion effects of two distinct ecosystems within the Wadden Sea, impacted by the bioinvasion of one species (ecosystem one) and ...
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Non parametric tests for 2 way anova and linear model? [duplicate]
My dissertation is due very soon and I have only just realised a large mistake in my work. I misread the normality test I used, which actually showed non normal data- but I still have homogeneity of ...
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In what ways is Gaussian Process Regression both parametric and non-parametric?
Gaussian Process Regression is considered a "non-parametric" model. However, the term "non-parametric" is often used imprecisely to mean different things, leading to questions ...
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Estimating Confidence in Feature Rankings from Multiple Experiments with Non-Normal Data
Hello dear Cross Validated Community,
I am a new doctoral student in bioinformatics, and I am working on a project involving multiple experiments, each generating a single numerical result for each of ...
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Non-Parametric Regression with an Omitted Variable
Suppose we use the Kernel Regression Estimator $$\hat{m}(c)=\frac{\sum_{i=1}^n K\left(\frac{x_i-c}{h}\right)y_i}{\sum_{i=1}^n K\left(\frac{x_i-c}{h}\right)}$$
where $h\to 0$ and $nh\to \infty$ as $n\...
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Singular Spectrum Analysis Decomposition on single input signal using PyTS module
I read this paper and was curious to apply it on a single-channel audio recording of mixed sources. It is about Singular Spectrum Analysis (SSA).
The paper mentions that a key component of the ...
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How to show $\sup_{x\in [a,b]}|f_n(x)-f(x)|=O_p(\sqrt{\frac{\log n}{nh}}+h^2)$ when the kernel $K(\cdot) $ is of bounded variation?
Consider the kernel estimate $f_n$ of a real univariate density defined by $$f_n(x)=\sum_{i=1}^{n}(nh)^{-1}K\left\{h^{-1}(x-X_i)\right\}$$
where $X_1,...,X_n$ are independent and identically ...
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Controlling for regression to the mean in nonparametric survey response data - pre-post design - difference between groups
I have 920 pre-post responses to 5-point Likert-scale questions evaluating the impact of an educational intervention. I wish to test whether outcomes (change = post - pre) differed across different ...
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Does the sign test only work on location families?
That is,
if $G$ is the distribution of the sample, what does it test:
\begin{align}
\mathcal H_0 : G(x) = F(x) && \mathcal H_1 : G(x) = F(x - \theta), \theta \neq 0
\end{align}
where $F$ is ...
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Strange results using Dunn's test [closed]
I am receiving a result that seems very counter-intuitive using the Dunn's test. My data is illustrated in the plot below. I have 5 groups (labelled muscle1a, muscle1b, muscle2, muscle3 and muscle4).
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Hoeffding’s formula for Locally most powerful rank tests
Suppose we have a testing problem with $$H_0: X_1,X_2, . . . ,X_n \ \text{are i.i.d. random variables with a continuous cdf} \ F(x) \ \text{and pdf} \ f(x)$$ and $$H_1: X_1,X_2, . . . ,X_n \ \text{are ...
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Can a Gaussian Process predict random events?
I know that we can use Gaussian processes effectively for function approximation and regression. However,suppose there is a sequence of points in time $S = \{s_1, s_2, \dots, s_n\}$, where $s_i$ can ...
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