N. M. Neykov

发表

The least trimmed quantile regression

Peter Filzmoser, N. M. Neykov, Pavel Cízek, 2012, Comput. Stat. Data Anal..

Application of a robust method for detecting outliers in data used for antineoplastic activity prediction

Ilza Pajeva, N. M. Neykov, P. N. Neytchev, 1993 .

Robust fitting of mixtures using the trimmed likelihood estimator

Peter Filzmoser, R. Dimova, N. M. Neykov, 2007, Comput. Stat. Data Anal..

Statistical Modeling of Hunting Success Using Hunter Surveys

Peter Filzmoser, N. M. Neykov, Jose Carlos Martinez Avila, 2016 .

Robust joint modeling of mean and dispersion through trimming

Peter Filzmoser, N. M. Neykov, P. N. Neytchev, 2012, Comput. Stat. Data Anal..

Generalized d-fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator with Application

N. M. Neykov, N. Neykov, R. Dimova, 2003 .

Breakdown Point and Computation of Trimmed Likelihood Estimators in Generalized Linear Models

Christine H. Müller, N. M. Neykov, C. Müller, 2003 .

Robust detection of discordant sites in regional frequency analysis

N. M. Neykov, P. N. Neytchev, P.H.A.J.M. van Gelder, 2007 .

Regional Frequency Analysis of Extreme Wave Heights: Trading Space for Time

Pieter van Gelder, N. M. Neykov, P. N. Neytchev, 2001 .

Robust two-group discrimination by bounded influence regression: a Monte Carlo simulation

N. M. Neykov, P. N. Neytchev, V. K. Todorov, 1994 .

MIXTURE OF GLMS AND THE TRIMMED LIKELIHOOD METHODOLOGY

Peter Filzmoser, N. M. Neykov, P. N. Neytchev, 2004 .

About Regression Estimators with High Breakdown Point

N. M. Neykov, N. Neykov, D. Vandev, 1998 .

Robust Selection of Variables in the Discriminant Analysis Based on MVE and MCD Estimators

N. M. Neykov, P. N. Neytchev, N. Neykov, 1990 .