Procedures that rely on relatively few assumptions about underlying probability distributions.

learn more… | top users | synonyms

0
votes
0answers
7 views

How to validate classifier (built by using MLN method)?

I have developed a method (let's call it Method X) that has a classifier function. The classifier function was built by using MLN (Markov logic network). I need to ...
1
vote
1answer
35 views

Is it reasonable to make inferences to the population from non-parametric tests?

I just had it put to me that one can not reasonably make inferences from non-parametric statistics. This strikes me as absurd as the logical rational supporting counter-factual resampling/rank order ...
0
votes
0answers
12 views

Bandwidth selection in multivariate semi parametric estimation in R (np package)

I am estimating a semi-parametric and a full non parametric model, by using the np package in R. I have more than 400 observations for T big years, moreover several ...
1
vote
0answers
34 views

Setting up a naiv tensor product B-spline example

I've simulated data according to $y = \text{sin}(2\cdot(4x-2))+2\cdot\text{exp}(-(16^2)(x-0.5)^2)+\epsilon$ where $\epsilon \sim \mathbb{N}(0,0.3^2)$ By evaluating the ith B-Spline of degree $k$, ...
4
votes
1answer
71 views
+50

Different non-parametric methods for estimating the probability distribution of data

I have some data and was trying to fit a smooth curve to it. However, I do not want to enforce too many prior beliefs or too strong pre-conceptions (except the ones implied by the rest of my question) ...
3
votes
0answers
40 views

Entropy estimation for a symbol sequence

I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the source entropy of a time-series consisting of a sequence of symbols. Rather than simply measuring ...
1
vote
0answers
14 views

repeated measures design between subjects with non normal and small N

I’m examining the effects of a parent-delivered reading intervention on 11 child outcome variables at 3 different time points (pre, post-intervention and follow-up) with a control group. Total sample ...
0
votes
0answers
14 views

Nonparametric Time Series Forecasting

I am trying to understand how Kernel Density Estimation (KDE) or (nonparametric) Quantile Regression can be used to forecast values given historical observations. For example, consider the following ...
3
votes
2answers
46 views

Compute moment and quantiles of a stream of data

I'd like to compute the moments and quantiles of a random variable which is the output of a sensor. I don't intend to store all the values this sensor outputs (let's say it outputs one value each 15 ...
5
votes
3answers
741 views

Is visual inspection the only way to compare large datasets?

I have two large data sets, in fact, one of them is even much larger than the other. Visually, there doesn't seem to be that much difference between them: The actual data underlying the box plot ...
1
vote
0answers
7 views

significant difference in mineral concentration between chemical analysis and values declared on packaging?

I want to find out whether there was any significant difference in mineral concentration between chemical analysis and values declared on packaging. After carrying out Shapiro-Wilk tests to assess ...
1
vote
1answer
24 views

Literature on nonparametric density estimation

I am about to write my bachelor thesis about non-parametric density estimation, especially kernel density estimators and their application in classification. As I am quite new to looking for academic ...
1
vote
0answers
11 views

Test which method is better if data is gathered on overlapping time windows (not independent)

I have two methods which are being used to estimate a specific signal. I have a ground truth measurement of this signal and these two methods are using noisy data to estimate this signal. This signal ...
0
votes
0answers
18 views

Statistics for catch of tuna longline

I have study on catch for tuna longline. In here I have 3 independent variables (number of hooks, length of branch line & baits) and 3 dependent variables (catch of tuna, catch of marlin & ...
1
vote
0answers
35 views

Is the Pearson goodness-of-fit test parametric or non-parametric?

In this question there was an interesting discussion concerning the Pearson goodness-of-fit test going on which was far from conclusive: Is there any statistical test that is parametric and ...
2
votes
1answer
63 views

What inferential method produces the empirical CDF?

The empirical cdf is an estimate of the cdf. What kind of estimation method (such as method of moments, MLE, ...) constructs the empirical cdf? Is the empirical cdf a nonparametric estimate? Do ...
0
votes
1answer
24 views

Non parametric one sample t-test alternative with a binary variable

I am doing an analysis of items (I1, I2, I3, etc.). The items could be either correctly answered (1) or incorrectly answered (0). Visually, most of the participants answered the items correctly. I ...
0
votes
0answers
24 views

Is pairwise wilcoxon test a valid non-parametric alternative to Tukey's HSD test?

I am trying to identify significant differences between groups from normal and non-normal distributions. When the distribution is normal the workflow is pretty straightforward: ANOVA and after that a ...
2
votes
1answer
17 views

Distribution heavily stacked on either limit - appropriate test?

I have two sets of results from an experiment that produces distributions with extremely heavily stacked sides and mostly uniform elsewhere. The aim of my analysis is to answer a the question roughly ...
0
votes
0answers
14 views

mixed between-within design when covariate-DV relationship is non-linear (quadratic)

My question is about what method to use for a mixed between-within design when the relationship between the covariate and the DV is non-linear (quadratic). My DV is reasoning task score. There are ...
1
vote
2answers
36 views

Paired t-test of medians

I need to run an inferential test on some large data where the individual data points have a heavily skewed distribution. I'm considering doing a paired t-test across a number of days comparing the ...
0
votes
1answer
50 views

What is a good transformation for data that looks like an S on the Q-Q plot? Or a good nonparametric alternative for correlations?

I am trying to do a study to determine if average annual temperature is related to number of cases of a particular disease. I have data for 15 different states over ten years. I have done multiple ...
2
votes
0answers
69 views

Non-parametric estimators for time-varying binomial proportion

I have a bunch of count data associated with time intervals (potentially overlapping and of variable lengths), say $(s_i, t_i, n_i, N_i)$ where $N_i$ is a count of the total number of events ...
1
vote
2answers
64 views

How to compare two non-normally distributed samples with very different sizes? (Mann-Whitney vs Randomization/Bootstrap)

Perhaps this is a very basic question, but I didn't find yet a simple solution for this simple problem: I want to compare two samples (say X and Y) for a continuous variable which is non-normally ...
1
vote
1answer
46 views

Confidence interval does not include 0, but Wilcoxon test is sgnificant

I've created an error plot with CI 95% to visualize the difference (post test - pre test) between achieved scores. n = 64 Judging from the confidence intervals one could conclude that there's is ...
0
votes
0answers
14 views

All vs all post-hoc after Aligned Friedman (k classifiers over multiple datasets)

I have k classifiers and n datasets, and I have only one accuracy measurement (which is actually the average of three independent repetitions of the 5-fold-CV, i.e. average over 15 accuracy values) ...
0
votes
0answers
79 views

How many people bought wine?

Rephrased a problem trying to solve for work in terms of people buying wine, also included progress made so far. Set-up: Customers enter a winery with the option of buying bottles of wine. Those who ...
1
vote
2answers
48 views

Probablistic counterpart for kNN

We know that the Gaussian Mixture Model is a probabilistic counterpart of k-means algorithm. Is there a probabilistic counterpart for kNN? (which is similar to k-means, but supervised.)
7
votes
3answers
137 views

Introduction to non-parametric statistics

I have been studying statistics for the past two years. Almost everything I have learnt is about parametric statistics. Now I would like to learn more about non-parametric statistics. Can anyone ...
0
votes
1answer
44 views

Is skewness always bad?

In my experiment, I hypothesised that individuals in one treatment condition would give higher values on a likert scale than individuals in the other treatment condition. It was a one tailed ...
4
votes
2answers
104 views

Deriving confidence interval from standard error of the mean when the data are non-normal

I have a small sample (n = 8), and I have calculated the mean and standard error of the mean. I don't know the underlying distribution of these observations, and I cannot assume it to be normal. I ...
0
votes
2answers
49 views

Goodness of fit tests robust against non-normality and estimated parameters

I'm struggling to find a goodness of fit test of the above. The non-parametric tests I have looked at (KS) seem to be unable to deal with estimated parameters - can someone help?
0
votes
0answers
24 views

Small Sample Size in Kernel Density Estimation

I am working on a problem where I have to solve an optimization problem over a dataset of 6 variables (~300 data points per variable). The data set is a historical data set, unfortunately it is small ...
2
votes
1answer
47 views

Kwallis2 insignificant - need for comparisons between the groups?

I have a question concerning the Kruskal-Wallis test. I compared 4 groups with the kwallis2 test (in stata) and got insignificant results (the multiple comparisons are aborted). When I look at the ...
1
vote
1answer
34 views

Non-parametric equality of means test

I'm looking to test for equality of means across different sample sizes of data, but know that the data is not normally distributed and heteroscedastic. Can anyone suggest anything?
0
votes
2answers
47 views

Do all my dependent variables have to be normal for a non-parametric assumption?

Im currently attacking SPSS, and I'm just testing for normality... In the Shapiro-Wilk Statistic test, my dependent variables have a wide range of significance levels. Obviously, I know that the sig. ...
2
votes
1answer
95 views

Hypothesis testing - Wilcoxon test, bootstrapping, or something else?

A colleague has developed a treatment for to "prevent falls" in cognitively impaired, psychiatric patients. Since this would be very useful treatment in this population, we especially do not want to ...
2
votes
0answers
15 views

Non-parametric 2-sample test for correlated data

I have two samples of data, S1 and S2, that both suffer from spatial autocorrelation. The samples are different sizes and are not paired (specifically, S1 is comprised of M subsamples of k spatially ...
0
votes
0answers
21 views

Correlating ranked lists

Let's assume I have 10 users who rank a list by preference. A B C etc. My questions are: What is the best statistical method to find which lists are the most correlated? If they are the same, ...
0
votes
1answer
51 views

Testing difference between two means. Skewed ( N1=21) vs Symmetric bell (N2=47). Wilcoxon rank sum test appropriate?

I need to test to compare the means of two samples, one with size 21 and the other with size 47. Histograms show Sample 1 is skewed to the right while Sample 2 has a bell symmetrical shape. ...
0
votes
1answer
47 views

Non-parametric test for comparing a function of two samples

The first thing that comes to mind when comparing some property of two samples is probably the independent samples t-test. Sometimes, people point out that this has the inherent assumption of the ...
0
votes
1answer
30 views

what kind of non-parametric test to use?

I collected data on one sample, the DV could be separated into two groups (success yes vs. no) and then I have several IVs with interval scale. I just don't know if to use Wilcoxon or Man-Whitney ...
14
votes
3answers
191 views

Statistical test for two distributions where only 5-number summary is known

I have two distributions where only the 5-number summary (minimum, 1st quartile, median, 3rd quartile, maximum) and sample size are known. Cntrary to the question here, not all data points are ...
0
votes
0answers
30 views

Is it meaningful to use Kolmogorov-Smirnov test in small sub sample?

I have a data set with around 14,000 observations. This is a sample data set not the population. I have fitted a model (based on fuzzy logic) based on this data. I have 27 actual values(from 14,000 ...
0
votes
0answers
56 views

Non-parametric correlation for continuous and dichotomous variables

I have two variables I want to test with correlation, one is continuous and the other dichotomous. My data are non-normally distributed, plus the variance is heterogeneous, so I have to apply a ...
0
votes
0answers
27 views

Is there a way to statistically differentiate parametric and count data?

I'm wondering whether there are any statistical properties that should differentiate count data and parametric data. In other words, is there an aspect of my data that I can analyze, or a test I can ...
3
votes
2answers
63 views

Estimate population quantiles from subpopulations' quantiles

Suppose there is a population partitioned arbitrarily into a set of subpopulations that completely cover the original population. Assume that for some variable, we know each subpopulation's quintiles ...
1
vote
1answer
36 views

Appropriate statistical measure for rank correlation

In the course of my work, something of a problem has arisen. It can be summarized like this: there's a large pool of job applicants, let's say N of them. What needs to be done is that these applicants ...
1
vote
2answers
83 views

How to compare multiple proportions between multiple groups

I measured prey capturing success (=proportion of successful captures divided by the total number of prey captured) in four fish species (species 1: n=19, species 2: n=18, species 3: n=4, species 4: ...
4
votes
1answer
89 views

The Effect of Outliers

The following question comes up in robust statistics. There are two formula indicated below that I do NOT know how to derive. However, in order to make the context clear, let's start with the easiest ...