Pages that link to "Item:Q1015895"

The following pages link to The stochastic approximation method for the estimation of a multivariate probability density (Q1015895):

Displaying 44 items.

• Estimation of probability density on the basis of the method of stochastic regularization (Q583765) (← links)
• Smooth distribution function estimation for lifetime distributions using Szasz-Mirakyan operators (Q825066) (← links)
• Nonparametric recursive estimation of the copula (Q826673) (← links)
• Nonparametric relative recursive regression (Q828048) (← links)
• Automatic bandwidth selection for recursive kernel density estimators with length-biased data (Q830250) (← links)
• On the use of stochastic approximation in recursive estimation (Q868978) (← links)
• Nonparametric recursive method for kernel-type function estimators for spatial data (Q1642437) (← links)
• Online estimation of hazard rate under random censoring (Q1642739) (← links)
• Data-driven bandwidth selection for recursive kernel density estimators under double truncation (Q1711618) (← links)
• Recursive non-parametric kernel classification rule estimation for independent functional data (Q1995821) (← links)
• Recursive density estimators based on Robbins-Monro's scheme and using Bernstein polynomials (Q1999984) (← links)
• Recursive nonparametric regression estimation for dependent strong mixing functional data (Q2023475) (← links)
• Data-driven deconvolution recursive kernel density estimators defined by stochastic approximation method (Q2023841) (← links)
• Moderate deviation principles for nonparametric recursive distribution estimators using Bernstein polynomials (Q2072236) (← links)
• The stochastic approximation method for recursive kernel estimation of the conditional extreme value index (Q2136049) (← links)
• Minimum Hellinger distance estimation for discretely observed stochastic processes using recursive kernel density estimator (Q2156008) (← links)
• Optimal bandwidth selection for recursive Gumbel kernel density estimators (Q2178952) (← links)
• On a class of recursive estimators for spatially dependent observations (Q2233584) (← links)
• The rate of complete consistency for recursive probability density estimator under strong mixing samples (Q2244465) (← links)
• A compact law of the iterated logarithm for online estimator of hazard rate under random censoring (Q2244598) (← links)
• Bandwidth selection for recursive kernel density estimators defined by stochastic approximation method (Q2260589) (← links)
• The stochastic approximation method for estimation of a distribution function (Q2261928) (← links)
• Bandwidth selection for the Wolverton-Wagner estimator (Q2301115) (← links)
• Recursive kernel density estimation and optimal bandwidth selection under \(\alpha\): mixing data (Q2322055) (← links)
• Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method (Q2322619) (← links)
• On the choice of smoothing parameters for semirecursive nonparametric hazard estimators (Q2323198) (← links)
• Approximation of probability density functions by the multilevel Monte Carlo maximum entropy method (Q2375153) (← links)
• The multivariate Révész's online estimator of a regression function and its averaging (Q2396740) (← links)
• Nonparametric recursive method for moment generating function kernel-type estimators (Q2667626) (← links)
• Methodology for nonparametric bias reduction in kernel regression estimation (Q2692996) (← links)
• Bias reduction in kernel density estimation (Q4643634) (← links)
• Nonparametric relative recursive regression estimators for censored data (Q4988562) (← links)
• Recursive asymmetric kernel density estimation for nonnegative data (Q5012343) (← links)
• Recursive kernel regression estimation under <i>α</i> – mixing data (Q5057323) (← links)
• Bandwidth selector for nonparametric recursive density estimation for spatial data defined by stochastic approximation method (Q5077234) (← links)
• Bernstein polynomial of recursive regression estimation with censored data (Q5090307) (← links)
• Large and moderate deviation principles for nonparametric recursive kernel distribution estimators defined by stochastic approximation method (Q5106688) (← links)
• (Q5114795) (← links)
• On the rates of asymptotic normality for recursive kernel density estimators under <i>ϕ</i>-mixing assumptions (Q5742400) (← links)
• Two new nonparametric kernel distribution estimators based on a transformation of the data (Q5861457) (← links)
• Recursive kernel estimator in a semiparametric regression model (Q5881429) (← links)
• Plug‐in bandwidth selector for recursive kernel regression estimators defined by stochastic approximation method (Q6063606) (← links)
• Nonparametric recursive estimation for multivariate derivative functions by stochastic approximation method (Q6133738) (← links)
• Semi-recursive kernel conditional density estimators under random censorship and dependent data (Q6587713) (← links)