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20212025
most citedTruncated, Censored, and Actuarial Payment-type Moments for Robust Fitting of a Single-parameter Pareto Distribution

13 citations · 29 across the 7 of their papers we have counts for

collaborators

9 papers

stat.ME2025

Robust and Computationally Efficient Trimmed L-Moments Estimation for Parametric Distributions

Chudamani Poudyal, Qian Zhao, Hari Sitaula

This paper proposes a robust and computationally efficient estimation framework for fitting parametric distributions based on trimmed L-moments. Trimmed L-moments extend classical…

stat.ME2024

-estimation of Claim Severity Models Weighted by Kumaraswamy Density

Chudamani Poudyal, Gokarna R. Aryal, Keshav Pokhrel

Statistical modeling of claim severity distributions is essential in insurance and risk management, where achieving a balance between robustness and efficiency in parameter estimat…

stat.ME2024

Robust Estimation of the Tail Index of a Single Parameter Pareto Distribution from Grouped Data

Chudamani Poudyal

Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However,…

math.ST2024

On the Asymptotic Normality of Trimmed and Winsorized L-statistics

Chudamani Poudyal

There are several ways to establish the asymptotic normality of -statistics, which depend on the choice of the weights-generating function and the cumulative distribution select…

stat.AP2023★ 4 cited

Credibility Theory Based on Winsorizing

Qian Zhao, Chudamani Poudyal

The classical Bühlmann credibility model has been widely applied to premium estimation for group insurance contracts and other insurance types. In this paper, we develop a robust B…

stat.ME2022★ 1 cited

Method of Winsorized Moments for Robust Fitting of Truncated and Censored Lognormal Distributions

Chudamani Poudyal, Qian Zhao, Vytaras Brazauskas

When constructing parametric models to predict the cost of future claims, several important details have to be taken into account: (i) models should be designed to accommodate dedu…

stat.ME2022

Robust Estimation of Loss Models for Truncated and Censored Severity Data

Chudamani Poudyal, Vytaras Brazauskas

In this paper, we consider robust estimation of claim severity models in insurance, when data are affected by truncation (due to deductibles), censoring (due to policy limits), and…

stat.ME2021★ 11 cited

Robust Estimation of Loss Models for Lognormal Insurance Payment Severity Data

Chudamani Poudyal

The primary objective of this scholarly work is to develop two estimation procedures - maximum likelihood estimator (MLE) and method of trimmed moments (MTM) - for the mean and var…

stat.ME2021★ 13 cited

Truncated, Censored, and Actuarial Payment-type Moments for Robust Fitting of a Single-parameter Pareto Distribution

Chudamani Poudyal

With some regularity conditions maximum likelihood estimators (MLEs) always produce asymptotically optimal (in the sense of consistency, efficiency, sufficiency, and unbiasedness)…