New low variance L-estimator for percentile estimation

Risto Suoranta; Kari-Pekka Estola

doi:10.1109/NDSP.1993.767688

New low variance L-estimator for percentile estimation

Risto Suoranta, Kari-Pekka Estola

VTT Technical Research Centre of Finland

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

In this paper percentile estimation and corresponding estimators are considered. A new order statistics based percentile estimator called Subset Averaged Percentile Estimate SAPE(L,q,r) and its special me Subset Averaged Median Estimate SAME(L,q) is presented. Proposed esti mators are compared to the set of well-known OS-filters. Results show that presented approach offers a new competent family of estimators to obtain robust and low-vari ance estimates of percentiles, including median.

Original language	English
Title of host publication	IEEE Winter Workshop on Nonlinear Digital Signal Processing
Place of Publication	Tampere
Publisher	IEEE Institute of Electrical and Electronic Engineers
Number of pages	6
ISBN (Print)	951-721-944-X
DOIs	https://doi.org/10.1109/NDSP.1993.767688
Publication status	Published - 1993
MoE publication type	A4 Article in a conference publication
Event	IEEE Winter Workshop on Nonlinear Digital Signal Processing - Tampere, Finland Duration: 17 Jan 1993 → 20 Jan 1993

Conference

Conference	IEEE Winter Workshop on Nonlinear Digital Signal Processing
Country/Territory	Finland
City	Tampere
Period	17/01/93 → 20/01/93

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10.1109/NDSP.1993.767688

Cite this

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title = "New low variance L-estimator for percentile estimation",

abstract = "In this paper percentile estimation and corresponding estimators are considered. A new order statistics based percentile estimator called Subset Averaged Percentile Estimate SAPE(L,q,r) and its special me Subset Averaged Median Estimate SAME(L,q) is presented. Proposed esti mators are compared to the set of well-known OS-filters. Results show that presented approach offers a new competent family of estimators to obtain robust and low-vari ance estimates of percentiles, including median.",

author = "Risto Suoranta and Kari-Pekka Estola",

note = "Project code: KAU2012; IEEE Winter Workshop on Nonlinear Digital Signal Processing ; Conference date: 17-01-1993 Through 20-01-1993",

year = "1993",

doi = "10.1109/NDSP.1993.767688",

language = "English",

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booktitle = "IEEE Winter Workshop on Nonlinear Digital Signal Processing",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

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T1 - New low variance L-estimator for percentile estimation

AU - Suoranta, Risto

AU - Estola, Kari-Pekka

N1 - Project code: KAU2012

PY - 1993

Y1 - 1993

N2 - In this paper percentile estimation and corresponding estimators are considered. A new order statistics based percentile estimator called Subset Averaged Percentile Estimate SAPE(L,q,r) and its special me Subset Averaged Median Estimate SAME(L,q) is presented. Proposed esti mators are compared to the set of well-known OS-filters. Results show that presented approach offers a new competent family of estimators to obtain robust and low-vari ance estimates of percentiles, including median.

AB - In this paper percentile estimation and corresponding estimators are considered. A new order statistics based percentile estimator called Subset Averaged Percentile Estimate SAPE(L,q,r) and its special me Subset Averaged Median Estimate SAME(L,q) is presented. Proposed esti mators are compared to the set of well-known OS-filters. Results show that presented approach offers a new competent family of estimators to obtain robust and low-vari ance estimates of percentiles, including median.

U2 - 10.1109/NDSP.1993.767688

DO - 10.1109/NDSP.1993.767688

M3 - Conference article in proceedings

SN - 951-721-944-X

BT - IEEE Winter Workshop on Nonlinear Digital Signal Processing

PB - IEEE Institute of Electrical and Electronic Engineers

CY - Tampere

T2 - IEEE Winter Workshop on Nonlinear Digital Signal Processing

Y2 - 17 January 1993 through 20 January 1993

ER -

New low variance L-estimator for percentile estimation

Abstract

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