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Questions tagged [parametric]

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

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Survival analysis using a mixture distribution in R?

I want to use a mixture of Gamma distribution as a parametric model for survival analysis on censored data using R. In the "flexsurv" package there are different distributions but I couldn't find a ...
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4 views

normality and selection of analyse

In a study of comparison between 3 groups, if some of my data sets are normally distributed and some are not, should I analyse my data using parametric test or non-parametric or a mixture of both ...
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9 views

Feature selection in parametric optimization

Let't say that $\theta$ is a vector or real numbers of the form $(\theta_1, \theta_2,\theta_3, ...,\theta_n)$ and $Obj(\theta)$ is a continuous function (objective function). Let's say that I want to ...
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19 views

Distance/Metric between two regression models?

I wonder if there is any theory or work about the "similarity" of two regression models. For example, if it is linear regression, the "similarity" could be defined by the l-2 distance between 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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3answers
170 views

In survival analysis, when should we use fully parametric models over semi-parametric ones?

This question is the counterpoint of the other question In survival analysis, why do we use semi-parametric models (Cox proportional hazards) instead of fully parametric models? Indeed, it clearly ...
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0answers
90 views

Parametric vs non-parametric machine learning methods

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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1answer
84 views

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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1answer
61 views

A question about hypothesis testing [closed]

Question I am actually finding no clue how to start with this sum. Please help. Thank you.
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1answer
22 views

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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1answer
34 views

Pearson correlation coefficient: Gaussian data expected?

The Pearson correlation coefficient is sometimes referred to as a parametric statistic. Does this parametric nature imply that it is actually only applicable to data drawn from Gaussian distributions?
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1answer
17 views

What statistical method will I use if I want to compare 10 caloric values of rice samples to a suggested amount?

We've conducted a comparative study on the caloric values of rice sample from different food stalls found within our university and we want to compare it to a suggested caloric value of per-meal rice ...
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1answer
25 views

Integrating out an extra parameter in Maximum Liklihood estimation

In estimation theory I have seen maximum likelihood being used assuming additive Gaussian AWGN where the signal is a function of multiple parameters(like frequency, time delay, phase, bit). Sometimes ...
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2answers
51 views

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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1answer
73 views

Non-monotone hazard functions

I should start with the caveat that I am relatively new to Survival analysis. I was watching a Hulu documentary about Crocodiles last night, and they mentioned that baby crocodiles have a low chance ...
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0answers
19 views

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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6 views

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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14 views

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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32 views

Which parametric test to use for normality

I am writing a paper on the impact of a PLC (a specific type of education reform effort) on student performance outcomes. The IV is the PLC and the DV are the performance outcomes (AIMS Test Scores). ...
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2answers
117 views

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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1answer
48 views

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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1answer
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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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1answer
45 views

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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1answer
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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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3answers
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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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0answers
31 views

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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1answer
186 views

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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1answer
332 views

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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4answers
142 views

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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2answers
37 views

Likelihood term in Bayesian inferencing versus the general definition

In general we say that the likelihood function is defined as some $L(\theta|x)$, so that it is a function over some parameters: $\theta$ given some data: $x$. That is, $\theta$ is free to vary whilst $...
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48 views

MLE Asymptotics of Two independent samples

Given two independent samples, parameterized by the same parameter yet with different distributions (for example, Exponential(lambda) and Gamma(lambda, 2)), under what conditions is the parametric MLE ...
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0answers
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Dau Genton test - in grandmothers terms

tl;dr Can you explain the Dau Genton test in terms a median grandmother could understand? Background: So I am looking for an "in.chull" for multivariate, concave hull, and I was going through "...
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1answer
49 views

mixing non-parametric correlation and parametric regression

I'm running both correlational and regression analyses on a variable that is not normally distributed: For correlations, I decided to use Spearman's rank correlation (which is non-parametric) due to ...
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1answer
211 views

Is there a loss function when estimating a model using MCMC?

I am trying to understand how fitting a model using MCMC works. Is there a loss function that is optimized? Or is it simply a case of more draws from the distribution amount to a more complete ...
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Reference request for parametric bootstrapping theory [duplicate]

Where is a good reference for the theory behind parametric bootstrapping (use MLE estimates as parameters of a distribution,then simulate from that distribution using those estimates as true values)? ...
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1answer
158 views

How to calculate mortality rate or probability of death at time t for various parametric distributions, e.g. Weibull, exponential, log-normal

If I have lambda and gamma, can I estimate that the probability of death at time t, based on a Weibull distribution is: What are similar formulas for the exponential, Gompertz, log-normal, log-...
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63 views

For MVN, zero covariance implies independence. How about other distributions?

According to this page on wikipedia, if $X\sim N(\mu,\Sigma)$ with $\mu\in\mathbb R^2$ and $\Sigma\in\mathbb R^{2\times2}$ then we have $\textrm{Cov}(X_1,X_2)=0\implies X_1\perp\!\!\!\perp X_2$. Is ...
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1answer
63 views

Linear combo of normals is normal; how about other distributions?

We know that univariate normal distributions are independent only if their every linear combination is itself normal: $$\tag{1} Z_i\sim N(\mu_i,\sigma_i^2)\,(\forall i) \implies\\ \biggl( \textrm{...
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1answer
127 views

minimax estimator

In the lecture here https://www.stat.berkeley.edu/~yuekai/201b/lec6.pdf we have "minimaxity does not imply admissibility: a minimax estimator has the best worst-case performance, but its ...
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63 views

Nonlinear regression: improving parameter estimates

I'm running a nonlinear regression to estimate $\delta$ and $\alpha$ using the following model, where $X$, $Y$ and $Z$ are the variables: \begin{equation} Z = \left(\delta X^\alpha+(1-\delta)Y^\alpha\...
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34 views

Problems when estimating Valuet-at-risk and Expected Shortfall using log-return in parametric approach?

I have not much knowledge about statistics. One paper indicates that estimating VAR, ES using log-return would create problem in parametric approach. Therefore, people should use simple return of ...
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209 views

Type of parameter of the chi-squared distribution

Chi-squared distribution $\chi^2(k)$ has parameter $k$. On the one hand, $k$ should be the shape parameter because chi-squared distribution is a special case of Gamma distribution: $\chi^2(k) \equiv ...
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242 views

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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3answers
790 views

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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1answer
73 views

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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3answers
162 views

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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191 views

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 ...