# Questions tagged [semiparametric]

Semiparametric probability models are a general class of models used for estimation and inference that contain a nonparametric component and a parametric component.

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### Is the Wilcoxon two-sample test maximally powered to detect proportional odds alternatives?

We know from the literature that The Wilcoxon-Mann-Whitney two-sample rank sum test is optimal for detecting simple location shifts when comparing two continuous random variables that each have a ...
13 views

### Productivity estimator

I wanted to estimate the productivity parameter in the production function. I estimated it using levinsohn and petrin (lp) method. It is a semi-parametric regression estimation. It takes raw material ...
23 views

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### Why are my PITs (probability of integral transforms) not uniform?

community! I have here hope not a silly R code where I try to use PITs (probability of integral transforms) to "diagnose" fit of a simulated distribution. Code starts here: ...
50 views

### Quadratic regressions with explanatory count variables

I am running an OLS model where my dependent variable Y is continous and among the explanatory vars I have a count variable X. I want to test if the effect of X on Y changes sing. To do so I would ...
3k views

### Gam with low E.D.F (estimated degrees of freedom) value in main effect, not interaction term

I have a gam model with the following structure: ...
241 views

### JuliaOpt Empirical Likelihood Estimation

I am trying to perform an empirical likelihood estimation in a regression setting using JuliaOpt (Convex or JuMP) and ran into difficulties using either API. The problem: Empirical likelihood for ...
904 views

### Understanding Big/Little $O_p$/$o_p$ Notation for Estimators

I am reading a Text about Single Index Models (SIM), where a SIM is defined as $E[Y|X=x] = G(X' \beta)$, with $G$ and $\beta$ unknown. After proposing an estimator for the function $G$, the ...
91 views

### Density Function Estimation

Given a sample of $n$ observations, which are assumed to be $i.i.d.$ and generated from a continuous probability law. Consider the question of estimating the density function $f(x)$. There are two ...
204 views

### Testing semi-parametric versus parametric model

I am estimating a (semi)parametric and a parametric model for a panel data set, and I want to test the functional form by applying the method proposed by Henderson et al. (2008, p.267). In particular, ...
1k views

### Generalized additive models — who does research on them besides Simon Wood?

I use GAMs more and more. When I go to provide references for their various components (smoothing parameter selection, various spline bases, p-values of smooth terms), they are all from one ...
903 views

### Book for introductory nonparametric econometrics/statistics

My work implies a lot of econometrics, and I had a good formation about it. Nevertheless, I am regularly faced with some semi or non parametric techniques (for instance I had to use quantile ...
90 views

### Implementation of semi parametric methods

Has anyone worked with semi parametric methods to estimate parameters with binary outcome? Examples are like Cosslett (1983) or Ichimura or Klein-Spady. In other words we are looking for semi ...
727 views

### Variance of plugin estimator

This question related to my previous question. Let $$X_1,\dots,X_n$$ are i.i.d. with distribution function $F$ and $$Y_1,\dots,Y_n$$ are i.i.d. with distribution function $G$. Suppose that there ...