• Title/Summary/Keyword: squared residual

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A Empirical Study on the Developments of Pay Satisfaction Measurements (임금만족 측정치 개발에 관한 실증적 연구)

  • 이광희
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.54
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    • pp.119-128
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    • 2000
  • This study develops the pay satisfaction questionnaire for Korean employees. Based upon the review of previous studies, 16 questionnaire items are developed. Exploratory factor analysis results in a modified measurement through item deletion, item-to-dimension reassignment, and dimension combination. The measurement model was good fit assessed by overall fit measures(GFI; goodness of fit index, AGFI; adjusted goodness of fit index, RMR; root mean square residual) criteria, lambda score, and squared multiple correlation with confirmatory factor analysis. Implication of this work for future theoretical and empirical development are suggested.

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An Incompressible Flow Computation by a Hierarchical Iterative and a Modified Residual Method (계층적 반복과 수정 잔여치법에 의한 비압축성 유동 계산)

  • Kim J. W.
    • Journal of computational fluids engineering
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    • v.9 no.3
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    • pp.57-65
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    • 2004
  • The incompressible Navier-Stokes equations in two dimensions are stabilized by a modified residual method, and then discretized by hierarchical elements. The stabilization is necessary to escape from the Ladyzhenskaya-Babuska-Brezzi(LBB) constraint and hence to achieve an equal order formulation. To expedite a standard iterative method such as the conjugate gradient squared(CGS) method, a preconditioning technique called the Hierarchical Iterative Procedure(HIP) has been applied. In this paper, we increased the order of interpolation within an element up to cubic. The hierarchical elements have been used to achieve a higher order accuracy in fluid flow analyses, but a proper efficient iterative procedure for higher order finite element formulation has not been available so far The numerical results by the present HIP for the lid driven cavity flow and others showed the present procedure to be stable, very efficient and useful in flow analyses in conjunction with hierarchical elements.

Estimator of Mean Residual Life for Some Parametric Families Using Censored Data

  • Cho, Byung Yup;Choi, Kuey Chung;Choi, Sook Hee;Son, Young Nam
    • Journal of Korean Society for Quality Management
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    • v.23 no.2
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    • pp.80-90
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    • 1995
  • In this paper we consider a new estimator of mean residual life(MRL) under the random censorship model, based on the partial moment of the distribution. The parameters of a partial moment are estimated by its maximum likelihood estimators when the underlying distribution is known. Though the new estimator is not a consistent estimator of the MRL, it is shown to have smaller mean squared error than the well known empirical MRL estimator for a parametric family. We also compare the proposed estimator with some other estimators in terms of MSE for exponential and lognormal distributions using censored data.

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Bootstrap-Based Test for Volatility Shifts in GARCH against Long-Range Dependence

  • Wang, Yu;Park, Cheolwoo;Lee, Taewook
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.495-506
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    • 2015
  • Volatility is a variation measure in finance for returns of a financial instrument over time. GARCH models have been a popular tool to analyze volatility of financial time series data since Bollerslev (1986) and it is said that volatility is highly persistent when the sum of the estimated coefficients of the squared lagged returns and the lagged conditional variance terms in GARCH models is close to 1. Regarding persistence, numerous methods have been proposed to test if such persistency is due to volatility shifts in the market or natural fluctuation explained by stationary long-range dependence (LRD). Recently, Lee et al. (2015) proposed a residual-based cumulative sum (CUSUM) test statistic to test volatility shifts in GARCH models against LRD. We propose a bootstrap-based approach for the residual-based test and compare the sizes and powers of our bootstrap-based CUSUM test with the one in Lee et al. (2015) through simulation studies.

Adaptive Equalization Algorithm of Enhanced CMA using Minimum Disturbance Technique (최소 Disturbance 기법을 적용한 향상된 CMA 적응 등화 알고리즘)

  • Kang, Dae-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.6
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    • pp.55-61
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    • 2014
  • This paper related with the ECMA (Enchanced CMA) algorithm performance which is possible to simultaneously compensation of the amplitude and phase by appling the minimum disturbance techniques in the CMA adatpve equalizer. The ECMA can improving the gradient noise amplification problem, stability and roburstness performance by the minimum disturbance technique that is the minimization of the equalizer tap weight variation in the point of squared euclidiean norm and the decision directed mode, and then the now cost function were proposed in order to simultaneouly compensation of amplitude and phase of the received signal with the minimum increment of computational operations. The performance of ECMA algorithm was compared to present MCMA by the computer simulation. For proving the performance, the recovered signal constellation that is the output of equalizer output signal and the residual isi and Maximum Distortion charateristic and MSE learning curve that are presents the convergence performance in the equalizer and the overall frequency transfer function of channel and equalizer were used. As a result of computer simulation, the ECMA has more better compensation capability of amplitude and phase in the recovered constellation, and the convergence time of adaptive equalization has improved compared to the MCMA.

Sparse Signal Recovery with Parallel Orthogonal Matching Pursuit and Its Performances (병렬OMP 기법을 통한 성긴신호 복원과 그 성능)

  • Park, Jeonghong;Jung, Bang Chul;Kim, Jong Min;Ban, Tae Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.8
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    • pp.1784-1789
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    • 2013
  • In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the orthogonal matching pursuit (OMP) which has been widely used as a greedy algorithm for sparse signal recovery. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the firest iteration, (2) the conventional OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP outperforms than the existing sparse signal recovery algorithms in terms of exact recovery ratio (ERR) for sparse pattern and mean-squared error (MSE) between the estimated signal and the original signal.

Parameter Calibration of Storage Function Model and Flood Forecasting (1) Calibration Methods and Evaluation of Simulated Flood Hydrograph (저류함수모형의 매개변수 보정과 홍수예측 (1) 보정 방법론과 모의 홍수수문곡선의 평가)

  • Song, Jae Hyun;Kim, Hung Soo;Hong, Il Pyo;Kim, Sang Ug
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1B
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    • pp.27-38
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    • 2006
  • The storage function model (SFM) has been used for the flood forecasting in Korea. The SFM has a simple calculation process and it is known that the model is more reasonable than linear model because it considers non-linearity of flood runoff. However, the determination of parameters is very difficult. In general, the trial and error method which is an manual calibration by the decision of a model manager. This study calibrated the parameters by the trial and error method and optimization technique. The calibrated parameters were compared with the representative parameters which are used in the Flood Control Centers in Korea. Also, the evaluation indexes on objective functions and calibration methods for the comparative analysis of simulation efficiency. As a result, the Genetic Algorithm showed the smallest variation in objective functions and, in this study, it is known that the objective function of SSR (Sum of Squared of Residual) is the best one for the flood forecasting.

Supremacy of Realized Variance MIDAS Regression in Volatility Forecasting of Mutual Funds: Empirical Evidence From Malaysia

  • WAN, Cheong Kin;CHOO, Wei Chong;HO, Jen Sim;ZHANG, Yuruixian
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.7
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    • pp.1-15
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    • 2022
  • Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against the established Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the less explored but robust STES (Smooth Transition Exponential Smoothing) methods. (2) comparing forecast error performance between realized variance and squared residuals measures as a proxy for actual volatility. Data of seven private equity mutual fund indices (generated from 57 individual funds) from two different time periods (with and without financial crisis) are applied to 21 models. Robustness of the post-sample volatility forecasting of all models is validated by the Model Confidence Set (MCS) Procedures and revealed: (1) The weekly RVar-MIDAS model emerged as the best model, outperformed the robust DAILY-STES methods, and the weekly DAILY-GARCH models, particularly during a volatile period. (2) models with realized variance measured in estimation and as a proxy for actual volatility outperformed those using squared residual. This study contributes an empirical approach to one-week ahead volatility forecasting of mutual funds return, which is less explored in past literature on financial volatility forecasting compared to stocks volatility.

Comparison study on kernel type estimators of discontinuous log-variance (불연속 로그분산함수의 커널추정량들의 비교 연구)

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.1
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    • pp.87-95
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    • 2014
  • In the regression model, Kang and Huh (2006) studied the estimation of the discontinuous variance function using the Nadaraya-Watson estimator with the squared residuals. The local linear estimator of the log-variance function, which may have the whole real number, was proposed by Huh (2013) based on the kernel weighted local-likelihood of the ${\chi}^2$-distribution. Chen et al. (2009) estimated the continuous variance function using the local linear fit with the log-squared residuals. In this paper, the estimator of the discontinuous log-variance function itself or its derivative using Chen et al. (2009)'s estimator. Numerical works investigate the performances of the estimators with simulated examples.

Discontinuous log-variance function estimation with log-residuals adjusted by an estimator of jump size (점프크기추정량에 의한 수정된 로그잔차를 이용한 불연속 로그분산함수의 추정)

  • Hong, Hyeseon;Huh, Jib
    • The Korean Journal of Applied Statistics
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    • v.30 no.2
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    • pp.259-269
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    • 2017
  • Due to the nonnegativity of variance, most of nonparametric estimations of discontinuous variance function have used the Nadaraya-Watson estimation with residuals. By the modification of Chen et al. (2009) and Yu and Jones (2004), Huh (2014, 2016a) proposed the estimators of the log-variance function instead of the variance function using the local linear estimator which has no boundary effect. Huh (2016b) estimated the variance function using the adjusted squared residuals by the estimated jump size in the discontinuous variance function. In this paper, we propose an estimator of the discontinuous log-variance function using the local linear estimator with the adjusted log-squared residuals by the estimated jump size of log-variance function like Huh (2016b). The numerical work demonstrates the performance of the proposed method with simulated and real examples.