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Computing confidence intervals for output oriented DEA models: an application to agricultural research in Brazil. Repositório Alice
SOUZA, G. da S. e; SOUZA, M. O. de; GOMES, E. G..
We define and model the research production at Embrapa, the major Brazilian institution responsable for applied agricultural research. The main theoretical framework is Data Envelopment Analysis - DEA. We explore the economic interpretation and the statistical properties of these models to compute confidence intervals for output oriented efficiency measurements, based on a parametric flexible model, defined by the truncated normal distribution. These results provide a better insight on the efficiency classification and allow comparison among the DMUs involved int ehe evaluation process taking into account inefficiency random variation.
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Confidence intervals; DEA; Agricultural research.
Ano: 2009 URL: http://www.alice.cnptia.embrapa.br/handle/doc/659417
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Confidence intervals for rank statistics: Somers' D and extensions AgEcon
Newson, Roger.
Somers’ D is an asymmetric measure of association between two variables, which plays a central role as a parameter behind rank or nonparametric statistical methods. Given predictor variable X and outcome variable Y , we may estimate DYX as a measure of the effect of X on Y , or we may estimate DXY as a performance indicator of X as a predictor of Y. The somersd package allows the estimation of Somers’ D and Kendall’s τα with confidence limits as well as p-values. The Stata 9 version of somersd can estimate extended versions of Somers’ D not previously available, including the Gini index, the parameter tested by the sign test, and extensions to left- or right-censored data. It can also estimate stratified versions of Somers’ D, restricted to pairs in the...
Tipo: Journal Article Palavras-chave: Somersd; Somers' D; Kendall's τ_a; Harrell's c; ROC area; Gini index; Population-attributable risk; Rank correlation; Rank-sum test; Wilcoxon test; Sign test; Confidence intervals; Nonparametric methods; Propensity score; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/117583
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Confidence intervals for the kappa statistic AgEcon
Reichenheim, Michael E..
The command kapci calculates 100(1 - α)% confidence intervals for the kappa statistic using an analytical method in the case of dichotomous variables or bootstrap for more complex situations. For instance, kapci allows estimating CI for polychotomous variables using weighted kappa or for cases in which there are more than 2 raters/replications.
Tipo: Journal Article Palavras-chave: Kapci; Reliability; Kappa statistic; Confidence intervals; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116269
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Confidence intervals for the variance component of random-effects linear models AgEcon
Bottai, Matteo; Orsini, Nicola.
We present the postestimation command xtvc to provide confidence intervals for the variance components of random-effects linear regression models. This command must be used after xtreg with option mle. Confidence intervals are based on the inversion of a score-based test (Bottai 2003).
Tipo: Journal Article Palavras-chave: Xtvc; Variance components; Confidence intervals; Score test; Random-effects linear models; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116270
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From the help desk: Some bootstrapping techniques AgEcon
Poi, Brian P..
Bootstrapping techniques have become increasingly popular in applied econometrics and other areas. This article presents several methods and shows how to implement them using Stata’s bootstrap command.
Tipo: Journal Article Palavras-chave: Bssize initial; Bssize refine; Bssize analyze; Bssize cleanup; Bootstrap; Confidence intervals; Percentile-t; Dependent processes; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116251
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GEOSTATISTICAL MODELING OF SOYBEAN YIELD AND SOIL CHEMICAL ATTRIBUTES USING SPATIAL BOOTSTRAP REA
Dalposso,Gustavo H.; Uribe-Opazo,Miguel A.; Johann,Jerry A.; Bastiani,Fernanda De; Galea,Manuel.
ABSTRACT The goal of this study was to use the spatial bootstrap method to model the spatial dependence structure of soybean yield and soil chemical attributes in an agricultural area. The study involved developing confidence intervals in probability plots to determine the probability distributions assumed by the data; determine the empirical distributions of the semivariances and model parameters, allowing to obtain statistics and confidence intervals; and to construct maps for the variables. The quantile-quantile plots indicated that the data follows a normal distribution. The confidence intervals for the semivariances helped to model the spatial dependence structure, and the descriptive statistics of the bootstrap replicates of the model parameters...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Confidence intervals; Quantile-quantile plot; Resampling; Spatial dependence.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000300350
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Mejora de la calidad de procesos industriales mediante simulación y optimización. Colegio de Postgraduados
Estrada Drouaillet, Benigno.
En la industria es común realizar experimentos para optimizar los procesos de producción; sin embargo, se requieren de considerables recursos económicos y tiempo para desarrollar las nuevas tecnologías. La propuesta en este trabajo es emplear las técnicas de simulación Monte Carlo y bootstrap, para disminuir costos y tiempo en la optimización de procesos. Para lograr este propósito se emplearon la optimización aleatoria, la optimización no lineal NLM (Non-Linear Minimization) y la optimización Taguchi. Estas optimizaciones se compararon con el diseño inicial a través de los índices de capacidad del proceso y la función de pérdida de Taguchi. Los índices de capacidad , e índices ISO fueron simulados con Monte Carlo y sus respectivos intervalos de...
Palavras-chave: Simulación Monte Carlo; Bootstrap; Indices de capacidad; Intervalos de confianza; Optimización aleatoria; Taguchi; Monte Carlo Simulation; Capability indices; Confidence intervals; Random optimization; Maestría; Estadística.
Ano: 2010 URL: http://hdl.handle.net/10521/113
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Mejora de la calidad de procesos industriales mediante simulación y optimización. Colegio de Postgraduados
Estrada Drouaillet, Benigno.
En la industria es común realizar experimentos para optimizar los procesos de producción; sin embargo, se requieren de considerables recursos económicos y tiempo para desarrollar las nuevas tecnologías. La propuesta en este trabajo es emplear las técnicas de simulación Monte Carlo y bootstrap, para disminuir costos y tiempo en la optimización de procesos. Para lograr este propósito se emplearon la optimización aleatoria, la optimización no lineal NLM (Non-Linear Minimization) y la optimización Taguchi. Estas optimizaciones se compararon con el diseño inicial a través de los índices de capacidad del proceso y la función de pérdida de Taguchi. Los índices de capacidad , e índices ISO fueron simulados con Monte Carlo y sus respectivos intervalos de...
Palavras-chave: Simulación Monte Carlo; Bootstrap; Indices de capacidad; Intervalos de confianza; Optimización aleatoria; Taguchi; Monte Carlo Simulation; Capability indices; Confidence intervals; Random optimization; Maestría; Estadística.
Ano: 2010 URL: http://hdl.handle.net/10521/113
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Parameters behind “nonparametric” statistics: Kendall's tau, Somers' D and median differences AgEcon
Newson, Roger.
So-called “nonparametric” statistical methods are often in fact based on population parameters, which can be estimated (with confidence limits) using the corresponding sample statistics. This article reviews the uses of three such parameters, namely Kendall’s τα Somers’ D, and the Hodges–Lehmann median difference. Confidence intervals for these are demonstrated using the somersd package. It is argued that confidence limits for these parameters, and their differences, are more informative than the traditional practice of reporting only p-values. These three parameters are also important in defining other tests and parameters, such as the Wilcoxon test, the area under the receiver operating characteristic (ROC) curve, Harrell’s C, and the Theil median slope.
Tipo: Journal Article Palavras-chave: Confidence intervals; Gehan test; Harrell's C; Hodges–Lehmann median difference; Kendall's tau; Nonparametric methods; Rank correlation; Rank-sum test; ROC area; Somers' D; Theil median slope; Wilcoxon test; Research Methods/ Statistical Methods.
Ano: 2002 URL: http://purl.umn.edu/115950
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Speaking Stata: Correlation with confidence, or Fisher's z revisited AgEcon
Cox, Nicholas J..
Ronald Aylmer Fisher suggested transforming correlations by using the inverse hyperbolic tangent, or atanh function, a device often called Fisher’s z transformation. This article reviews that function and its inverse, the hyperbolic tangent, or tanh function, with discussions of their definitions and behavior, their use in statistical inference with correlations, and how to apply them in Stata. Examples show the use of Stata and Mata in calculator style. New commands corrci and corrcii are also presented for correlation confidence intervals. The results of using bootstrapping to produce confidence intervals for correlations are also compared. Various historical comments are sprinkled throughout.
Tipo: Article Palavras-chave: Corrci; Corrcii; Correlation; Confidence intervals; Fisher's z; Transformation; Bootstrap; Mata; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122603
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Statistical approaches in weed research: choosing wisely. Repositório Alice
CONCENCO, G.; ANDRES, A.; SCHREIBER, F.; SCHERNER, A.; BEHENCK, J. P..
bitstream/item/182633/1/Germani-Concenco-RBH-Revisao-Estatistica2018.pdf
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Multiple mean comparison; Statistical bias; Confidence intervals; Regression analysis.
Ano: 2018 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1095281
Registros recuperados: 11
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