Results 251 to 260 of about 231,426 (276)

NONPARAMETRIC AUTOCOVARIANCE FUNCTION ESTIMATION

Australian Journal of Statistics, 1997
SummaryNonparametric estimators of autocovariance functions for non‐stationary time series are developed. The estimators are based on straightforward nonparametric mean function estimation ideas and allow use of any linear smoother (e.g. smoothing spline, local polynomial).
Hyndman, R. J., Wand, M. P.
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Nonparametric e-Mixture Estimation

Neural Computation, 2016
This study considers the common situation in data analysis when there are few observations of the distribution of interest or the target distribution, while abundant observations are available from auxiliary distributions. In this situation, it is natural to compensate for the lack of data from the target distribution by using data sets from these ...
Takano, Ken, Hino, Hideitsu, Akaho, Shotaro, Murata, Noboru   +3 more
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Nonparametric Bayesian Interval Estimation

Biometrika, 1979
SUMMARY Bayesian confidence bands for a distribution function are converted into confidence intervals for specified population quantiles and also for the mean. Bayesian tolerance limits are similarly constructed.
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*Nonparametric Estimation

2022
Felix Abramovich, Ya’acov Ritov
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Nonparametric Curve Estimation

2016
This chapter provides an introduction to nonparametric estimations of densities and regression functions by the kernel method.
Rabi Bhattacharya, Lizhen Lin, Victor Patrangenaru   +2 more
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Nonparametric Geostatistical Estimation

1981
The reader will probably have seen no necessary connection between the contents of Chapters 2 and 3. Nevertheless, most of the nonparametric principles and methods introduced in Chapter 3 may be used to ease the constraints imposed on geostatistical techniques by assumptions of distribution and spatial homogeneity.
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Kernel Nonparametric Estimation

2008
Some regression models are fully parametric in that both the regression function and the error term distribution are parametrically specified, whereas some are semiparametric in the sense that only the regression function is parametrically specified—LSE is semiparametric in this sense.
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Nonparametric Curve Estimation

2004
In this Chapter we discuss nonparametric estimation of probability density functions and regression functions which we refer to as curveestimation or smoothing.
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Nonparametric Estimation

2013
Jianguo Sun, Xingqiu Zhao
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