Results 61 to 70 of about 229,123 (176)
Nonparametric estimation by convex programming
, 2009 The problem we concentrate on is as follows: given (1) a convex compact set $X$ in ${\mathbb{R}}^n$, an affine mapping $x\mapsto A(x)$, a parametric family $\{p_{\mu}(\cdot)\}$ of probability densities and (2) $N$ i.i.d.
Juditsky, Anatoli B. +1 more
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Efficiency of Average Treatment Effect Estimation When the True Propensity Is Parametric
Econometrics, 2019 It is well known that efficient estimation of average treatment effects can be obtained by the method of inverse propensity score weighting, using the estimated propensity score, even when the true one is known.
Kyoo il Kim
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Adaptive orthogonal series estimation in additive stochastic regression models [PDF]
In this paper, we consider additive stochastic nonparametric regression models. By approximating the nonparametric components by a class of orthogonal series and using a generalized cross-validation criterion, an adaptive and simultaneous estimation ...
Howell Tong, Jiti Gao, Rodney C Wolff
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Nonparametric Renewal Function Estimation
The Annals of Statistics, 1986 The renewal function is a basic tool used in many probabilistic models and sequential analysis. Based on a random sample of size n, a nonparametric estimator of the renewal function is introduced. Asymptotic properties of the estimator such as consistency and asymptotic normality are developed.
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SPECIES: An R Package for Species Richness Estimation
Journal of Statistical Software, 2011 We introduce an R package SPECIES for species richness or diversity estimation. This package provides simple R functions to compute point and confidence interval estimates of species number from a few nonparametric and semi-parametric methods.
Ji-Ping Wang
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Nonparametric Estimation of the Tail-Dependence Coefficient
Revstat Statistical Journal, 2013 A common measure of tail dependence is the so-called tail-dependence coefficient. We present a nonparametric estimator of the tail-dependence coefficient and prove its strong consistency and asymptotic normality in the case of known marginal ...
Marta Ferreira
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Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies [PDF]
A number of studies have explored the semi- and nonparametric estimation of stochastic frontier models by using kernel regression or other nonparametric smoothing techniques. In contrast to popular deterministic nonparametric estimators, these approaches
Kortelainen, Mika
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Nonparametric Change-Point Estimation
The Annals of Statistics, 1988 Consider a sequence of independent random variables $\{X_i: 1 \leq i \leq n\}$ having cdf $F$ for $i \leq \theta n$ and cdf $G$ otherwise. A class of strongly consistent estimators for the change-point $\theta \in (0, 1)$ is proposed. The estimators require no knowledge of the functional forms or parametric families of $F$ and $G$. Furthermore, $F$ and
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NPCirc: An R Package for Nonparametric Circular Methods
Journal of Statistical Software, 2014 Nonparametric density and regression estimation methods for circular data are included in the R package NPCirc. Specifically, a circular kernel density estimation procedure is provided, jointly with different alternatives for choosing the smoothing ...
María Oliveira +2 more
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Jackknife Estimator of Species Richness with S-PLUS
Journal of Statistical Software, 2005 An estimate of the number of species, S , usually called species richness by ecologists, in an area is one of the basic statistics used to ascertain biological diversity. Traditionally ecologists have used the number of species observed in a sample, S0 ,
Christina D. Smith, Jeffrey S. Pontius
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