Home Itens selecionados Provedores de dados OAI Créditos Sobre Ajuda

			Busca avançada
	Provedor de dados AgEcon (3) Autor Linhart, Jean Marie (3) Pitblado, Jeffrey S. (2) Gutierrez, Roberto G. (1) Hassell, James (1) Palavra-chave Research Methods/ Statistical Methods (3) Binary (1) Denormalized number (1) Double precision (1) Format (1) Hexadecimal (1) IEEE 754 (1) Kaplan–Meier (1) Kernel (1) Local linear (1) Local polynomial (1) Missing values (1) Normalized number (1) Overflow (1) Plugin (1) Smoothing (1) Stsatrisk (1) Subnormal number (1) Survival plots (1) Underflow (1) Mais... Tipo do documento Journal Article (2) Article (1) Ano 2008 (1) 2004 (1) 2003 (1) País United States (3) Idioma Inglês (3)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 3 Primeira ... 1 ... Última From the help desk: Kaplan–Meier plots with stsatrisk AgEcon Linhart, Jean Marie; Pitblado, Jeffrey S.; Hassell, James. stsatrisk is a wrapper for sts graph that adds a table to a survival plot with at-risk information, making it easy to create graphs that follow the list of recommendations given by Pocock et al. (2002) for Kaplan–Meier plots. We use stsatrisk to create plots in the desired format with the desired information. Tipo: Journal Article Palavras-chave: Stsatrisk; Kaplan–Meier; Survival plots; Research Methods/ Statistical Methods. Ano: 2004 URL: http://purl.umn.edu/116212 Mata Matters: Overflow, underflow and the IEEE floating–point format AgEcon Linhart, Jean Marie. Mata is Stata’s matrix language. The Mata Matters column shows how Mata can be used interactively to solve problems and as a programming language to add new features to Stata. In this quarter’s column, we investigate underflow and overflow and then delve into the details of how floating-point numbers are stored in the IEEE 754 floating-point standard. We show how to test for overflow and underflow. We demonstrate how to use the %21x format to see underflow and the %16H, %16L, %8H, and %8L formats for displaying the byte content of doubles and floats. Tipo: Article Palavras-chave: Underflow; Overflow; Denormalized number; Normalized number; Subnormal number; Double precision; Missing values; IEEE 754; Format; Binary; Hexadecimal; Research Methods/ Statistical Methods. Ano: 2008 URL: http://purl.umn.edu/122590 From the help desk: Local polynomial regression and Stata plugins AgEcon Gutierrez, Roberto G.; Linhart, Jean Marie; Pitblado, Jeffrey S.. Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964) and Watson (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local means, but local polynomial smooths have better statistical properties. The computational complexity may, however, be alleviated by using a Stata plugin. In this article, we describe the locpoly command for performing local polynomial regression. The calculations involved are implemented in both ado-code and with a plugin, allowing the user to assess the speed improvement obtained from using the plugin. Source code for the plugin is also provided as part of the... Tipo: Journal Article Palavras-chave: Local polynomial; Local linear; Smoothing; Kernel; Plugin; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116196 Registros recuperados: 3 Primeira ... 1 ... Última

Empresa Brasileira de Pesquisa Agropecuária - Embrapa Todos os direitos reservados, conforme Lei n° 9.610 Política de Privacidade Área restrita		Embrapa Parque Estação Biológica - PqEB s/n° Brasília, DF - Brasil - CEP 70770-901 Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco