Results 231 to 240 of about 606,425 (294)

Intercept Estimation of Semi-Parametric Joint Models in the Context of Longitudinal Data Subject to Irregular Observations. [PDF]

Biom J
Ledesma L, Pullenayegum E.
europepmc   +1 more source

Semiparametric efficient estimation of small genetic effects in large-scale population cohorts. [PDF]

Biostatistics
Labayle O, Roskams-Hieter B, Slaughter J, Tetley-Campbell K, van der Laan MJ, Ponting CP, Beentjes SV, Khamseh A.   +7 more
europepmc   +1 more source

Toward LLM-aware software effort estimation: a conceptual framework. [PDF]

Front Artif Intell
Alaswad F, Poovammal E, Aljaddouh B.
europepmc   +1 more source

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On parametric density estimation

Biometrika, 1989
Let p(x,\(\vartheta)\) be the density of a random variable x. A random sample \(s_ n=(x_ 1,...,x_ n)\) of size n is available from the distribution. By y a future observation from this distribution is denoted. Two distinct methods of estimating p(y\(| \vartheta)\) are known. The estimative method uses \[ p(y| {\hat \vartheta}_ n)=p(y| \vartheta ={\hat \
El-Sayyad, G. M., Samiuddin, M., Al-Harbey, A. A.   +2 more
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Non-parametric estimates of overlap

Statistics in Medicine, 2001
Kernel densities provide accurate non-parametric estimates of the overlapping coefficient or the proportion of similar responses (PSR) in two populations. Non-parametric estimates avoid strong assumptions on the shape of the populations, such as normality or equal variance, and possess sampling variation approaching that of parametric estimates.
R A, Stine, J F, Heyse
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Parametric Estimation from Weighted Samples

Biometrical Journal, 2001
Summary: We obtain parameter estimators based on length (size) biased samples for different models. We compare the estimators and Fisher's information from usual samples and length biased samples. Moreover, we obtain the estimators based on two samples, one unbiased and another one biased. We obtain a similar study for samples from a renewal process.
Navarro, Jorge, Ruiz, Jose M., del Aguila, Yolanda   +2 more
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Parametric and Nonparametric FDR Estimation Revisited

Biometrics, 2006
Summary Nonparametric and parametric approaches have been proposed to estimate false discovery rate under the independent hypothesis testing assumption. The parametric approach has been shown to have better performance than the nonparametric approaches. In this article, we study the nonparametric approaches and quantify the underlying relations between
Wu, Baolin, Guan, Zhong, Zhao, Hongyu
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Parametric Surface Estimation

1993
A parametric surface estimation algorithm is examined. The algorithm is a perfect interpolator. The points surrounding the point to be estimated are weighted according to the length of their paths from the point to be estimated, and not their Euclidean distance from that point.
E. A. Yfantis, G. T. Flatman, F. Miller
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Parametric Spectral Estimation

2002
Purpose The use of the periodogram empirical spectrum estimator or of the smoothed periodogram is not well-suited to some situations, in particular when only a small number of autocovariance coefficients of the process being studied are available from the observation.
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