• 제목/요약/키워드: Nonparametric Estimation

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ML estimation using Poisson HGLM approach in semi-parametric frailty models

  • Ha, Il Do
    • Journal of the Korean Data and Information Science Society
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    • 제27권5호
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    • pp.1389-1397
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    • 2016
  • Semi-parametric frailty model with nonparametric baseline hazards has been widely used for the analyses of clustered survival-time data. The frailty models can be fitted via an auxiliary Poisson hierarchical generalized linear model (HGLM). For the inferences of the frailty model marginal likelihood, which gives MLE, is often used. The marginal likelihood is usually obtained by integrating out random effects, but it often requires an intractable integration. In this paper, we propose to obtain the MLE via Laplace approximation using a Poisson HGLM approach for semi-parametric frailty model. The proposed HGLM approach uses hierarchical-likelihood (h-likelihood), which avoids integration itself. The proposed method is illustrated using a numerical study.

선형 평활스플라인 함수 추정과 적용 (A Linear Smoothing Spline Estimation and Applications)

  • 윤용화;김경무;김종태
    • Journal of the Korean Data and Information Science Society
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    • 제9권1호
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    • pp.29-36
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    • 1998
  • 본 논문은 Eubank (1994, 1997)에 의해 이론적으로 제안된 선형 평활스플라인 추정량에 대한 알고리즘을 개발함으로 선형 스플라인의 추정을 보다 쉽고 효율적으로 사용할 수 있도록 하는데 목적이 있다. 이 알고리즘을 이용하여 여러가지 모형의 예들에 대하여 추정량의 적합성을 조사하였고, 제시된 선형 평활스플라인 추정량이 비모수 함수 추정의 도구로서 잘 적합됨을 알 수 있었다.

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Model Averaging Methods for Estimating Implied and Local Volatility Surfaces

  • Kim, Nam-Hyoung;Lee, Jae-Wook;Han, Gyu-Sik
    • Industrial Engineering and Management Systems
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    • 제8권2호
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    • pp.93-100
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    • 2009
  • In this paper, we review widely used methods to extract local volatility surfaces (LVSs) from implied volatility surfaces (IVSs) and suggest a model averaging method for constructing implied and local volatility surfaces weighted by trading volumes. It makes use of model averaging method by means of bandwidth priors, and then produces a robust LVS estimation. The method is shown to provide the information about the confidence interval of estimators as well as a rather less variable weighted mean value for the IVS and LVS. To show the merits of our proposed method, we conduct simulations on equity-linked warrants (ELWs) with reasonable and acceptable results.

SOME PROPERTIES OF SIMEX ESTIMATOR IN PARTIALLY LINEAR MEASUREMENT ERROR MODEL

  • Meeseon Jeong;Kim, Choongrak
    • Journal of the Korean Statistical Society
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    • 제32권1호
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    • pp.85-92
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    • 2003
  • We consider the partially linear model E(Y) : X$^{t}$ $\beta$+η(Z) when the X's are measured with additive error. The semiparametric likelihood estimation ignoring the measurement error gives inconsistent estimator for both $\beta$ and η(.). In this paper we suggest the SIMEX estimator for f to correct the bias induced by measurement error, and explore its properties. We show that the rational linear extrapolant is proper in extrapolation step in the sense that the SIMEX method under this extrapolant gives consistent estimator It is also shown that the SIMEX estimator is asymptotically equivalent to the semiparametric version of the usual parametric correction for attenuation suggested by Liang et al. (1999) A simulation study is given to compare two variance estimating methods for SIMEX estimator.

Fixed-accuracy confidence interval estimation of P(X > c) for a two-parameter gamma population

  • Zhuang, Yan;Hu, Jun;Zou, Yixuan
    • Communications for Statistical Applications and Methods
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    • 제27권6호
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    • pp.625-639
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    • 2020
  • The gamma distribution is a flexible right-skewed distribution widely used in many areas, and it is of great interest to estimate the probability of a random variable exceeding a specified value in survival and reliability analysis. Therefore, the study develops a fixed-accuracy confidence interval for P(X > c) when X follows a gamma distribution, Γ(α, β), and c is a preassigned positive constant through: 1) a purely sequential procedure with known shape parameter α and unknown rate parameter β; and 2) a nonparametric purely sequential procedure with both shape and rate parameters unknown. Both procedures enjoy appealing asymptotic first-order efficiency and asymptotic consistency properties. Extensive simulations validate the theoretical findings. Three real-life data examples from health studies and steel manufacturing study are discussed to illustrate the practical applicability of both procedures.

Volatility and Z-Type Jumps of Euro Exchange Rates Using Outlying Weighted Quarticity Statistics in the 2010s

  • Yi, Chae-Deug
    • Journal of Korea Trade
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    • 제23권2호
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    • pp.110-126
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    • 2019
  • Purpose - This paper examines the recently realized continuous volatility and discrete jumps of US Dollar/Euro returns using the frequency of five minute returns spanning the period from February 2010 through February 2018with periodicity filters. Design/Methodology - This paper adopts the nonparametric estimation. The realized volatility and Realized Outlying Weighted variations show non-Gaussian, fat-tailed, and leptokurtic distributions. Some significant volatility jumps in returns occurred from 2010 through 2018, and the very exceptionally large and irregular jumps occurred around 2010-2011, after the EU financial crisis, and 2015-2016. The outliers occurred somewhat frequently around the years of 2015 and 2016. Originality/value - When we include periodicity filters of volatility such as MAD, Short Half Scale, and WSD, the five minute returns of US Dollar/Euro exchange rates have smaller daily jump probabilities by 20-30% than when we do not include the periodicity filters of volatility. Thus, when we consider the periodicity filters of volatility such as MAD, Short Half Scale, and WSD, the five minute returns of US Dollar/Euro have considerably smaller jump probabilities.

비선형 상태공간 모델을 위한 Point-Mass Filter 연구 (A Study on the Point-Mass Filter for Nonlinear State-Space Models)

  • 최영권
    • 산업기술연구
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    • 제43권1호
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    • pp.57-62
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    • 2023
  • In this review, we introduce the non-parametric Bayesian filtering algorithm known as the point-mass filter (PMF) and discuss recent studies related to it. PMF realizes Bayesian filtering by placing a deterministic grid on the state space and calculating the probability density at each grid point. PMF is known for its robustness and high accuracy compared to other nonparametric Bayesian filtering algorithms due to its uniform sampling. However, a drawback of PMF is its inherently high computational complexity in the prediction phase. In this review, we aim to understand the principles of the PMF algorithm and the reasons for the high computational complexity, and summarize recent research efforts to overcome this challenge. We hope that this review contributes to encouraging the consideration of PMF applications for various systems.

모수, 비모수, 베이지안 출산율 모형을 활용한 합계출산율 예측과 비교 (A comparison and prediction of total fertility rate using parametric, non-parametric, and Bayesian model)

  • 오진호
    • 응용통계연구
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    • 제31권6호
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    • pp.677-692
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    • 2018
  • 최근 2017년 우리나라 합계출산율은 1.05명로 2005년 1.08명 수준으로 회귀하는 현상을 보이고 있다. 1.05명은 인구대체선(2.1명), 안전선(1.5명)과도 거리가 먼 초저출산 수준이고 마치 초저출산 덫에 빠질 우려가 있다. 이에 합계출산율의 합리적인 예측과 이를 통한 출산정책에 유용한 자료를 제공하는 것은 그 어느 때 보다도 중요하다. 그 동안 다양한 통계적 방법으로 합계출산율 추이를 예측하였는데, 데이터 완비성이 높고 품질이 좋은 경우 모형 접근인 모수적 방법, 데이터 추이가 단절되거나 변동이 심한 경우 평활과 가중치를 적용한 비모수적 방법, 데이터 부족과 품질 등으로 선진국의 출산율 3단계 전이현상을 참고하여 이들의 사전분포를 활용하는 베이지안 방법 등이 적용되어 왔다. 본 연구는 최근 변동이 심한 우리나라 출산율에 모수, 비모수, 그리고 베이지안 방법을 적용하여 추정과 예측을 실시하고 도출된 결과 비교를 통해 적합성과 타당성 측면에서 어떤 방법이 합리적인지 모색하고자 한다. 분석결과 합계출산율 예측값 순위는 통계청 합계출산율이 가장 높고, 베이지안, 모수, 비모수 순으로 나타났다. 2017년 TFR 1.05명 수준을 감안할 때 모수, 비모수모형으로 도출된 합계출산율 예측값이 합리적이다. 또한 출산율 자료완비성이 높고 품질이 우수할 경우 계산 효율성과 적합도 관점에서 모수적 추정과 예측 접근 방법이 타 방법보다 우수한 것으로 도출되었다.

Bootstrap Estimation for the Process Incapability Index $C_{pp}$

  • Han, Jeong-Hye;Cho, Joong-Jae;Lim, Chun-Sung
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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    • pp.309-315
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    • 1998
  • Process Capability can be expressed with a process index which indicates the incapability of a process to meet its specifications. This index is regarded as a process capability index(PCI) or more precisely as a process incapability index(PII). It is obtained from a simple transformation of a PCI. Greenwich and Jahr-Schaffrath(1995) considered the PII $C_{pp}$ which could be obtained from the transformation to the PCI, $C_{pm}$, and they provided the asymptotic distribution for $C_{pp}$ which was useful unless the process characteristic was normally distributed. However, some statistical inferences based on the asymptotic distribution need a large sample size. There are some processes which process engineers could not help obtaining sufficiently a large sample size. Thus, we have derived its corresponding bootstrap asymptotic distribution since bootstrapping would be a helpful technique for the PII, $C_{pp}$ which was nonparametric or free from assumptions of the distribution of the characteristic X. Moreover, we have constructed six bootstrap confidence intervals used in reducing bias of estimations based on the bootstrap asymptotic distribution and simulated their performances for $C_{pp}$,

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Source Identification and Estimation of Source Apportionment for Ambient PM10 in Seoul, Korea

  • Yi, Seung-Muk;Hwang, InJo
    • Asian Journal of Atmospheric Environment
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    • 제8권3호
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    • pp.115-125
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    • 2014
  • In this study, particle composition data for $PM_{10}$ samples were collected every 3 days at Seoul, Korea from August 2006 to November 2007, and were analyzed to provide source identification and apportionment. A total of 164 samples were collected and 21 species (15 inorganic species, 4 ionic species, OC, and EC) were analyzed by particle-induced x-ray emission, ion chromatography, and thermal optical transmittance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified nine sources and the average mass was apportioned to secondary nitrate (9.3%), motor vehicle (16.6%), road salt (5.8%), industry (4.9%), airborne soil (17.2 %), aged sea salt (6.2%), field burning (6.0%), secondary sulfate (16.2%), and road dust (17.7%), respectively. The nonparametric regression (NPR) analysis was used to help identify local source in the vicinity of the sampling area. These results suggest the possible strategy to maintain and manage the ambient air quality of Seoul.