Questions tagged [parametric]

Statistical models described by a finite number of real-valued parameters. Often used in contrast to non-parametric statistics.

249 questions
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Patton's Symmetric Joe-Clayton copula

I am currently trying to apply Patton's Symmetric Joe-Clayton Copula, described in his "Modelling Asymmetric Exchange Rate Dependence". I am currently looking for the closed-form relation (if there is ...
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Covariance matrix in Gompertz paramteric survival model [on hold]

I would like to ask R for the covariance matrix of this Gompertz survival model: ...
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Confidence regions after fitting a 2 parameter gaussian mixture model?

Suppose I have a gaussian mixture model with 2 parameters $(u,v)$ and 2 parts. The model is $P({x_i}|u,v)=uN(x_i|\mu_1^{i} = x_i^2/v,\sigma_1^{i}) + (1-u)N(x_i|\mu_2^{i} = x_i^3/2v^2,\sigma_2^i)$. ...
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Prediction of regression coefficients with XGBoost

I am doing survival analysis. There is a dataset of items (id, group_id, observed lifetime, censorship status), each item belongs to a certain group. Each item is ...
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Parametric or non parametric test

I want to compare trends of R&D expenditures before and after a crisis. I was planning to use a paired T-test or a non-parametric alternative. But, before of that, I tested the data for normality. ...
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How could I estimate the quantiles of an unknown CDF?

I have been given with a set of data, which is supposedly come from an unknown distribution F. And I am asked to propose a suitable parametric or nonmparametric estimator for quantiles q(α) =F⁻¹(α) ...
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How does variation in the effect size affects power?

Effect size The effect size affect the power of a statistical test. We typically summarizes the magnitude of the effect of a variable as a single number (which we call the effect size). To my ...
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Chi-Square 2x2 Contingency vs z-test for two proportions: parametric or non-parametric?

Chi-Square Test I think it is generally agreed upon that the Chi-square test (specifically, the chi-square test for a 2-by-2 contingency table) is a non-parametric test. (Though there is the ...
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Why is “condensed nearest neighbour” Parametric? [duplicate]

Definition of "condensed nearest neighbour", at training time it chooses the c "best" training examples (where c is a hyper-parameter), and at test time uses the usual KNN prediction but based only on ...
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Confused about the statistical tests to choose or any transformation to apply

I am new to the stackexchange, so please forgive me for my editing ignorance. I am confused and stuck about how to proceed further with my data. I have the following data ...
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Parametric vs non-parametric machine learning methods [duplicate]

I looked-up many references and websites and researched on how to determine if a method is between parametric or non-parametric. I came up with below definitions, A parametric algorithm has a fixed ...
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Why is the correlation coefficient parametric?

I am a little confused on the definition of "parametric". The book that I'm reading writes that "the correlation coefficient attempts to estimate a particular parameter in the Normal model for two ...
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Does statistical significance impact uplift calculation for marketing campaign

I'm trying to understand 2 things in relation to calculating uplift from a marketing email campaign: Impact of statistical significance Impact of highly skewed data on calculating uplift The ...
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Regression discontinuity - optimal bandwidth choice

I have a very basic question. I would like to implement a nonparametric RD but I have a Poisson outcome variable. I would like to select the proper bandwidth and my question is about which method to ...
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Sample size calculation for parametric test, with large effect expected, small numbers. Should I use parametric or non parametric tests?

I am trying to figure out what would be the best way to analyze data from a randomized double blind trial we conducted. We sought to find if two dosages of a drug were effective for a severe symptom ...
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is the PROCESS-test in statistics a parametric or non parametric test?

This might be a silly question. But my supervisor wants me to redo the analytical (spss) tests of my thesis, because my data is not normally distributed. I found that there is an alternative for the ...
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What is a good test for whether a sample is drawn from a particular parametric family against a generalized alternative

Suppose I have some large number n of draws from a strictly positive distribution that I believe to be a member of a particular parametric distributional family. I use the draws to estimate the ...
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Simulating the Posterior Density of a Transformed Parameters

I am reviewing an example (p. 180-181, Example 11.3 and 11.4) from All of Statistics by Larry Wasserman. The example intends to illustrate that the posterior can be found analytically and can be ...
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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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Can one use parametric regression tests (e.g., Pearson's R2) on summary statistics (that are normal) derived from non-normal data?

Can one use parametric linear regression tests (e.g., Pearson's R2) on summary statistics (e.g., mean and median) that are normal but derived from non-normal data? I am specifically dealing with mean ...
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comparison of two independent data of same location using statistical test

I have elevation values of a geographical area with their lattitude and longitude, derived from two different satellites. How can I compare these data using some statiscal test?
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Is there a commonly accepted effect size parameter for pairs of Bernoulli processes?

Let $f(x|\rho)$ be the Bernoulli pmf with probability $\rho$ of success. \begin{align} f(x|\rho) = \left\{ \begin{array}{ll} \rho & x = 1 \\ 1-\rho & x=0 \end{array} \right....
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Repeated Measures ANOVA with two factors

I have 300 patients with heart problems (2 groups/types of problem) that have completed the questionnaire SF-36 (8 scales), before and after the surgery. Some of them have been attending sessions with ...
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How is an RNN (or any neural network) a parametric model?

I'm going through this paper A Multi-Horizon Quantile Recurrent Forecaster. The authors state that: 3.1. Loss Function In Quantile Regression, models are trained to minimize the total ...
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Confused on normality assumption

I know that the sampling distribution of the mean can be assumed to be normal if N>30, but does this have an implication on the "30" itself (the sample data)? I have three different time series with ...
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Derive probability distributions from i.i.d. Gumbel

I have a question on how to derive (if possible) the following probability distributions. Consider 3 random variables $(X,Y,Z)$ mutually independent and identically distributed. Specifically, $X$ is ...
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Parametric tests for non-normal data?

I'm trying to polish my stats skills and it seems to me that you have either parametric test for normal data, or non-parametric tests for non-normal data. Looking at the t-test for instance, I don't ...
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Coefficient of variation (CV) of log-transformed data

I understand that with log-transformed data, the coefficient of variation (CV) on the original scale is equal to sqrt(exp(sigma^2)-1), where sigma is the standard ...
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Why use parametric test at all if non parametric tests are 'less strict'

I have read from several sources, even in my undergrad courses, that parametric tests require the data to have a certain distribution, for instance normal, whilst non-parametric don't. I have ...
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Types of parameters of a parametric family of probability distributions

A statistical parameter is a quantity that indexes a family of probability distributions. Wikipedia has the following definition of a shape parameter: A shape parameter is any parameter of a ...
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Why do several (if not all) parametric hypothesis tests assume random sampling?

Tests like Z, t, and several others assume that the data is based on a random sampling. Why? Suppose that I'm doing experimental research, where I care much more for the internal validity than the ...
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Parametric survival with correlated predictors

I have observational data on censored failure data. I am trying to perform a Parametric Survival as a function of variable A and B, where A is the time spent under control strategy 1, and B is the ...
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Function of a sufficient statistic

It is well-known that a 1-1 function of a sufficient statistic is also sufficient for a parameter $p$. I am however confused by the consequence that if $T$ is sufficient for a parameter $p$, then a ...
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Does the definition of regular estimator depend on the rate of convergence? If not, should it?

The definition of regular estimator in my lecture notes is: Let $X_1^{(n)}, \dots, X_n^{(n)} \overset{iid}{\sim} P_n \sim \mathcal{P}(\Theta)$ where $\mathcal{P}(\Theta)$ is a regular parametric ...
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How to estimate the probability of team A with win percentage $P_a$ winning against team B with win percentage $P_b$?

Surely this sort of problem must have a name. Because it does not have a well defined answer, I am asking for (1) the name of this type of problem and (2) for general approaches to this question that ...
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How can the parameters be unknown but the probability distribution be known?

In an article (Nelson & Katzenstein, 2014) I came across the following sentence: ... “a fixed model of the economy with known parameters (or sometimes unknown parameters with known probability ...