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.
2,116
questions
0
votes
1
answer
181
views
What do these Wilcoxon values tell me?
I did a pre and post-test with a small number of students ($n=12$).These values came after a science intervention that took $4$ weeks. I used a Wilcoxon test for 2 related samples as there was not a ...
0
votes
0
answers
144
views
Comparing the output distribution of two ML models
Consider a regression task (e.g. predicting house prices) with a given train and test sets.
We start with constructing a linear regression model, in which we assume $y_i=X^T\beta+\epsilon$ with $E[\...
0
votes
0
answers
24
views
BART with non-parametric heteroscedastic noise?
Is there a variant of BART that robustly captures noise that is both heteroscedastic and non-parametric (or has an a-priori unknown parametric form)?
For example, a BART that could fit this test data:
...
1
vote
1
answer
33
views
Estimate multivariate distribution with several variables on real data (continuous and categoricals) and sample from it
I have a complex dataset, collected through a survey, with both continuous (such as Age, Body mass index, etc..) and categorical variables (i.e. Gender, Education, etc..). I want to estimate their ...
0
votes
1
answer
23
views
Choice of test for Comparing Chatbot vs. Group of Humans on Ordinal Scale
Background
I want to compare chatbot (e.g. ChatGPT) performance on medical questions with a group of human doctors. Each question will be answered and scored on an ordinal scale 1, 2, 3, 4 or 5. I ...
2
votes
2
answers
247
views
non-parametric-ANOVA
I have a dataset containing angles. They represent the bending angle that a seedling makes to go toward light. Genotype A is WT and A is the one we are testing. We removed a PKS gene, wich is ...
1
vote
2
answers
305
views
SIgnificant ANOVA but not significant post hoc ... what can I do?
I am analyzing some IHC data on the density of cells in two brain regions(factor 1) in two closely related species(factor 2). My data is composed of an n of 6 for each species and is not normally ...
0
votes
0
answers
48
views
Statistical Power Analysis for reight skewed data sets
I have price Data for a set of items for various time steps as i collect this data regularly. The data is very large (over 250000 items usualy per group per point in time) and not normaly dstributed ...
0
votes
0
answers
72
views
What is this nonparametric goodness-of-fit test?
I wrote down a goodness-of-fit test that I have not seen before.
However, it is quite elementary and has many applications, so I
bet it must have been known. Could someone tell me its name?
Setup. The ...
2
votes
1
answer
68
views
What non-parametric test for multivariate binary data should I use?
I have two different groups of participants ("g" and "b") answering the same set of questions. Group "g" answered questions in the same order. Group "b" ...
0
votes
0
answers
12
views
Statistical test for Likert scale perceptions of application of a HR development model to dental restorative specialty training
I'd be most grateful for some advice about suitable statistical testing for a research project.
It's a survey questionnaire to restorative specialty trainees and alumni trainees exploring the ...
1
vote
1
answer
66
views
How to estimate how heavy a tail is?
Suppose I have data coming from a single variate distribution. I want to estimate how heavy the tail of the distribution is. For example, if the data comes from the Zipf distribution, I would want the ...
1
vote
1
answer
49
views
Very small degrees of freedom when using yuen function in WRS2 package of R
I'm trying to run a number of independent samples t-tests. I'm using the yuen function in the WRS2 package because my data are non-normal and ordinal. My sample ...
0
votes
0
answers
25
views
Parametric or non parametric mixed effect models for very small sample size in ecological/soil data?
I am running an ecological/environmental experiment in a salt marsh with 5 experimental treatments and 3 replicate soil samples taken from each treatment. I have been taking measurements from these ...
0
votes
0
answers
62
views
Bayesian analysis of non-normally distributed variable
I would like to use an Bayesian approach to compare a continuous non-normally distributed variable taking values between -1 to 1 between two populations. The measurements are not paired.
Overall my ...
0
votes
0
answers
4
views
learning guarantees for gaussian weighting of training points
I have my training data for binary classification that consists of $N$ pairs $$(x_i\in R^F, y_i \in {-1, 1})$$ $i\in [1,\dots,N]$. My classification rule of a new point $x$ is simply
$$
\hat{y}(x) = \...
0
votes
0
answers
29
views
Boostrapping from Exponential Sample to estimate the quantiles
I have the problem where I want to estimate the quantiles of a distribution by bootstrapping. Fortunately I do know the original DGP which I chose to be an Exp(1/4) distribution and so the theoretical ...
0
votes
0
answers
19
views
How do I use bootstrapping to compare more than two means?
I'm trying to use non-parametric bootstrapping to compare mean values in a 2 (between) by 4 (within) experimental design. I cannot use mixed ANOVA because the sample values are not normally ...
1
vote
0
answers
28
views
Complete Statistic for a family with finite r-th moment
Consider the family of all continuous distributions with finite $r$-th moment (where $r \geq 1$ is a given integer). We denote this family as, $$\mathscr{P}_r=\left\{f:f \ \text{is a pdf and} \int|x|^...
1
vote
0
answers
49
views
The hunt for a 'nice' flexible distribution [duplicate]
Background
Suppose I have data $\mathcal{D}_1, \cdots, \mathcal{D}_n$ with each $\mathcal{D}_i$ containing $m$ observations $X_{i1}, \cdots, X_{im}$; these observations are of unknown distribution, ...
1
vote
0
answers
30
views
Strong consistency of kernel density estimator
I am studying the book Nonparametric and Semiparametric Models written by Wolfgang Hardle and have difficulty with the following exercise:
$\textbf{Exercise 3.13}$ Show that $\hat{f_h}^{(n)}(x) \...
2
votes
2
answers
360
views
How could Lilliefors use Monte Carlo if the estimand is not distribution-free?
Lilliefors test is a well-known statistical test for normality. Its idea is based on the Kolmogorov-Smirnov test, except the CDF is replaced by the CDF of the normal distribution with $\mu, \sigma^2$ ...
0
votes
0
answers
67
views
How to construct homogeneous subsets table for nonparametric tests?
Does post-hoc for friedman tests or nonparametric testshave like a homogeneous subset table from SPSS? Mean doesn't represent it well so I tried using median but my data was zero-inflated so the most ...
1
vote
2
answers
144
views
Parametric vs Non-parametric test recommendation
What type of non-parametric test would be suitable for the dataset shown in the image:
The sample size is 200 each for both variables. The data value can vary from 0-4 for both variables. The ...
0
votes
0
answers
17
views
Is there a method bias when I prefer a specific post-hoc that shows a significance after significance in test of difference in groups?
I'm working to see if a machine does better than a worker in terms measurement (by having a measurement from an expert be the control). So my dataframe contains the Measurement Value, Measuring Device,...
1
vote
0
answers
42
views
Why is histogram density estimation nonparametric?
My understanding of histogram density estimation:
For $k$ predefined equal-width bins $(b_0, b_1], (b_1, b_2], ..., (b_{k-1}, b_k]$ and $n$ observations $x_1,...,x_n \in (b_0,b_k]$, we estimate ...
3
votes
1
answer
685
views
I have applied many statistical tests to my data, but still cannot determine normality
I have run multiple tests to determine normality on my dataset, but I am unsure which one to adhere to, especially since my histograms, density plots, and QQ plots leave much to be desired in terms of ...
0
votes
0
answers
48
views
Multivariate analysis for non-normal variables
Edit: I am trying to produce a model in R in order to analyze the relationship between several variables. I am looking at the relationship between behaviour and dispersal of a population. Each ...
3
votes
1
answer
130
views
If I have a very small n for one group and a very large number of features, should I choose a parametric or a non-parametric test?
I have a dataset that contains human metabolite concetration in a fluid. One group has about 12 samples, while another only has 5. My question is if I can assume normality for this data and do ANOVA/t-...
2
votes
1
answer
110
views
Covariance between two binomial random variables or expectation of product of binomial random variables
I have an empirical distribution $S_n(x)$ (= proportion of samples less than equal to x) from a random sample $X_1, X_2, ..., X_n$ for a random variable $X \sim F_X$. Consider the random variable $T_n(...
0
votes
0
answers
20
views
GLMM not working if I specify the distribution as gamma
Following is the histogram and Q-Q plot of deceleration data retrieved from driving simulator experiment. As the data is not normally distributed, I am using generalized linear mixed model to analyze ...
0
votes
1
answer
48
views
Non-Parametric Test for Regression Significance
I have created a plot of the regression slope of sea surface temperatures (x) and an atmospheric variable (y). Although, I need to test the statistical significance of these trends using a non-...
1
vote
1
answer
44
views
Comparing data with opposite distributions
What test can I use to compare whether the difference between the following sets of data are significant.
I know, I can just look at them, but I'd like it to be a bit more scientific than that. The ...
0
votes
0
answers
59
views
How to determine significance for a Corrado rank test in an event study?
I apologise if this is a stupid question (it feels stupid tbh). I am currently doing an event study and my abnormal returns are not normally distributed. I am now in the process of performing a ...
0
votes
0
answers
17
views
Mixture of Conditional Random Variables by Sampling
I am struggling to put my transformation of data into mathematical contexts. My goal is to define a mapping that transforms the original data into some awkwardly mixed data. In my simulation study, I ...
3
votes
1
answer
88
views
Is this nonparametric tests with the same data valid?
I have 6 algorithms, and each algorithm I use on N problem instances (say N is around 200).
I divided the algos into two groups, 3 into group A and 3 into group B. They are divided into two groups ...
0
votes
0
answers
28
views
Understanding the bootstrapped method for calculating non-parametric p-values
I'm trying to understand the non-parametric bootstrapping to calculate p-values. I understand pearson correlation has it's own method for calculating p-values but I'm just using this as an example.
...
0
votes
0
answers
28
views
Anova violates normality assumption for error data
I have a 2 x 2 repeated measures ANOVA (N = 51) with Error Rate data as the dependent measure. The error data violates the normality assumption, even when outliers are removed. I have looked at the ...
1
vote
0
answers
34
views
Alternative to Bonferroni Correction for Dichotomous Variable? [closed]
I am working with a dichotomous variable and my supervisor has asked me to apply a Bonferroni correction to our data using SPSS. From my understanding, Bonferroni corrections are used when performing ...
1
vote
0
answers
19
views
Appropriate tests and normalization approaches for highly non-normal data
I'm trying to ascertain whether a particular type of article, $T$, is associated with higher engagement scores in academic journals, and how substantial the effect size might be. I have raw data of ...
2
votes
2
answers
151
views
Multiple regression on unpaired data (A~B+C)
I am not sure how to test one of my hypothesis from my data.
Basically, I have 3 behavioral measures A, B and C, and I want to test that A is a composite of B and C: A = B+C
However, for practical ...
1
vote
1
answer
102
views
OLR for non-normal continuous dependent variable with two categorical independent variables?
ID
Sex
Surface
B1
1
female
UN
1255
2
female
UN
542
3
female
UN
818
1
female
UN
274
2
female
UN
261
3
female
UN
314
1
female
UP
552
2
female
UP
548
3
female
UP
721
1
female
UP
431
2
female
...
1
vote
0
answers
134
views
Projection pursuit regression
Projection pursuit regression (PPR) is described in Hastie et al.'s The Elements of Statistical Learning in the chapter on neural networks. The algorithm was introduced by Friedman and Stuetzle (1981)....
2
votes
2
answers
97
views
How do I compare my data with the general population data in SPSS
My purpose is to compare my data with the general population data derived from a published report. I can only extract mean, median, 5th, 95th and 97.5th percentiles from it. Also, My data is non-...
0
votes
0
answers
7
views
Regression models that conform to functional groupings of features
For example, suppose we want to predict y with features x1, x2, x3, x4. If I specify
...
1
vote
1
answer
101
views
Can ANOVA suffice for comparing mean of percent/proportion data?
I've been handed off some data to analyze and I'm looking for something simple and straightforward. The 1 response variable/dependent variable is average percent mortality from 7 treatment groups (...
0
votes
0
answers
59
views
Dunn test in R: comparison between levels of a single factor in a 2-factor experiment
For a 2-factor experiment, the TukeyHSD function in R (after a significant ANOVA) can calculate P values for the differences between levels of a single factor (basically, comparisons between the ...
3
votes
1
answer
51
views
Bonferroni correction gives weird results in R
I have this dataset:
Treatment
data
T1
0
T1
0
T1
0
T10
0
T10
0
T10
0
T11
0.2
T11
0.2
T11
0.2
T12
0
T12
0
T12
0
T2
0.7
T2
0.6
T2
0.6
T3
0.8
T3
0.7
T3
0.8
T4
0.3
T4
0.3
T4
0.4
T5
...
1
vote
0
answers
24
views
Gaussian white noise model in application
I am interested in applications (to data) of non-parametric statistics, and my question concerned the Gaussian white noise model defined by,
$$
X_{t_1, \ldots, t_d}=f\left(t_1, \ldots, t_d\right) d ...
1
vote
1
answer
179
views
In an A/B test, how can you check if assignment to the various buckets was truly random?
Trying to figure out how I can confirm that my A/B Test assignment is truly random. I know the runs test is used to test for randomness.
Is it possible to use the runs test to check if my A/B Test ...