# Questions tagged [parameterization]

For questions about how to parameterize some statistical model, or comparisons between different ways to parameterize.

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### How to implement the estimation of parameters in negative binomial distribution in python?

Assuming the negative binomial distribution, How can I implement the estimation to parameters(r & p) especially by MLE? Which function or package should I use? scipy.stats, sympy?
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### Why is it easier to estimate $P(X|Y)$ rather than $P(Y|X)$ in terms of number of parameters?

In chapter 3 of the book by Mitchell ("Generative and discriminative classifiers: Naive Bayes and logistic regression") he states that "accurately estimating P(X|Y) typically requires many more ...
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### Starting values for an nls model in R [duplicate]

I'm trying to fit an exponential model using nls, but I don't know how to select the starting values for the parameters. I know this question has been answered multiple times, but I spent some days ...
1k views

### Fitting SIR model with 2019-nCoV data doesn't conververge

I am trying to calculate the basic reproduction number $R_0$ of the new 2019-nCoV virus by fitting a SIR model to the current data. My code is based on https://arxiv.org/pdf/1605.01931.pdf, p. 11ff: <...
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### parameterize distribution of subsets

Suppose there is a set $S=\{1, 2, 3, ..., n\}$, then I need a distribution of its subsets with fixed size k, which can be denoted as $A=\{x_1, x_2, ..., x_k\}$ where $x_1$ to $x_k$ are from 1 to n. ...
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### What is the definition of a scalar parameter?

I'm having trouble understanding what explicity is a scalar parameter. I understand what a location parameter and scale parameter represent but what exactly is the definition of a scalar parameter? ...
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### Why are decision trees (especially ID3) non-parametric?

I was going through the definition of parametric and non-parametric models. So the parametric are the ones which have a fixed number of parameters that you are trying to learn and this number is ...
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### State whether the model in question is parametric or non-parametric

The number of eggs laid by an insect follows a Poisson distribution with an unknown mean $\lambda$. Once laid, each egg has an unknown chance, $p$, of hatching and the hatching of one egg is ...
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### Choosing Gaussian PDF basis bandwidth depending on number of bases and range of data

Summary (details below!) I have a basis expansion of $m$ (univariate) Gaussian PDFs to model the density of a sample $X$. The means of these PDFs are spaced equidistantly through the domain of $X$ ...
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### Testing whether the conditional correlations/covariances differ between two groups

I have two samples of variables $\{y_{1i},y_{2i},x_i,s_i\}$. Where $y_1$ and $y_2$ are binary variables, $x$ is a continuous variable and $s$ is a sample indicator, taking the value 0 in one sample ...
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### How to find parameter $k$ from a negative binomial distribution in R?

I want to find the value of parameter $k$ from my data set. The data set is composed of several populations. Should I calculate the parameter $k$ for each subpopulation, or for the population at large?...
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### Can every parameter $\Theta$ in Bayesian modelling be explained via De Finettis representation theorem

My question is the following: I recently got to know (and love) De Finettis representation theorem and I now started to read a Book an Bayesian statistics. However this book simply takes as the ...
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### Correct understanding of De Finettis representation theorem

I am currently interestend in understanding De Finettis representation theorem. As I am only familiar with Frequentist thinking I have some problems to understand its meaning. I have already read the ...
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### How to identify a Bayesian SEM parameter in R package blavaan

I have fit a Bayesian SEM using the R package blavaan. ...
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### Why are mixed effect methods more effective when data are limited

In the study in here, it is said that mixed effects models are better in estimating parameters of a ODE system when there is only very small number of data to estimate the parameters. So, in a ...
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### From OLS to semi-parametric GAM: parametric vs no-parametric

I am quite new to this kind of topic, but for my master thesis i built an multiple linear regression with OLS. Now I want to control for non-linear relationships using a semi-parametric GAM. My ...
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### GLMMs, stable isotope distribution analysis

I am currently working with a set of samples of stable isotopic concentrations obtained from a group of individuals. I am trying to process this data through a glmm() from the package lme4 to ...
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### How to Interpret Parameter Estimate Output from SPSS [duplicate]

Dear Community Members, Given the outputs of the SPSS analysis, how can the exp (B ) and Beta values be interpreted in terms of odd ratio ? and in relation to how the independent variable affects the ...