• Title/Summary/Keyword: Fixed Effects

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A Bayesian inference for fixed effect panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.179-187
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    • 2016
  • The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

An Analysis on Vehicle Accident Factors of Intersections using Random Effects Tobit Regression Model (Random Effects Tobit 회귀모형을 이용한 교차로 교통사고 요인 분석)

  • Lee, Sang Hyuk;Lee, Jung-Beom
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.1
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    • pp.26-37
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    • 2017
  • The study is to develop safety performance functions(SPFs) for urban intersections using random effects Tobit regression model and to analyze correlations between crashes and factors. Also fixed effects Tobit regression model was estimated to compare and analyze model validation with random effects model. As a result, AADT, speed limits, number of lanes, land usage, exclusive right turn lanes and front traffic signal were found to be significant. For comparing statistical significance between random and fixed effects model, random effects Tobit regression model of total crash rate could be better statistical significance with $R^2_p$ : 0.418, log-likelihood at convergence: -3210.103, ${\rho}^2$: 0.056, MAD: 19.533, MAPE: 75.725, RMSE: 26.886 comparing with $R^2_p$ : 0.298, log-likelihood at convergence: -3276.138, ${\rho}^2$: 0.037, MAD: 20.725, MAPE: 82.473, RMSE: 27.267 for the fixed model. Also random effects Tobit regression model of injury crash rate has similar results of model statistical significant with random effects Tobit regression model.

The Influencing of Aging on Time Preference in Indonesia

  • KIM, Dohyung
    • The Journal of Industrial Distribution & Business
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    • v.12 no.8
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    • pp.33-39
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    • 2021
  • Purpose: The influence of age on time preference is not identified in the usual cross-sectional analysis. This study aims to test whether age affects time preference after controlling for the effects of individual heterogeneity including cohort effects. Research design, data and methodology: Drawing on a nationally representative panel dataset of Indonesians, we estimate the effects of age on time preference after controlling for unobserved individual heterogeneity as well as potential cohort effects. We measure time preference exploiting information on two sets of multiple price lists: one for a one-year delay, and the other for a five-year delay. Results: When we controlled for time-invariant individual characteristics, including birth cohort effects in a fixed effects model, the older men and women were more patient in a linear fashion, particularly when the delay was longer. To highlight the importance of controlling for individual fixed effects, we repeated the specification without controlling for individual fixed effects in OLS or censored maximum likelihood regression; we found no relation between age and impatience in men or women and for a one or five-year delay. Conclusions: The older men and women are more patient, and time preferences are correlated with unobserved individual heterogeneity.

Outbound Air Travel Demand Forecasting Model with Unobserved Regional Characteristics (미관찰 지역 특성을 고려한 내국인 국제선 항공수요 추정 모형)

  • YU, Jeong Whon;CHOI, Jung Yoon
    • Journal of Korean Society of Transportation
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    • v.36 no.2
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    • pp.141-154
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    • 2018
  • In order to meet the ever-increasing demand for international air travel, several plans are underway to open new airports and expand existing provincial airports. However, existing air demand forecasts have been based on the total air demand in Korea or the air demand among major cities. There is not much forecast of regional air demand considering local characteristics. In this study, the outbound air travel demand in the southeastern region of Korea was analyzed and the fixed-effects model using panel data was proposed as an optimal model that can reflect the inherent characteristics of metropolitan areas which are difficult to observe in reality. The results of model validation show that panel data analysis effectively addresses the spurious regression and unobserved heterogeneity that are difficult to handle in a model using only a few macroeconomic indicators with time series characteristics. Various statistical validation and conformance tests suggest that the fixed-effects model proposed in this study is superior to other econometric models in predicting demand for international demand in the southeastern region.

The Response of QTL in Generation during Selection (선발과정에서의 세대별 QTL 좌위 고정에 관한 연구)

  • Lee Ji-Woong
    • Journal of Embryo Transfer
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    • v.20 no.3
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    • pp.217-232
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    • 2005
  • The objective of this study was to determine the response of QTL in each generation during selection to develop inbred lines. The simulation program was written in Fortran. Magnitude of QTL effects, base population size, number of QTL assigned to population, and the allelic frequency for the positive allele at each major QTL were highly associated with number of generations to fixation of QTLs during selection. Populations with larger QTL effects and larger base population size had more individuals with fixed QTL. However, a smaller number of QTL assigned to population had a higher fraction of individuals with fixed QTL at each generation compared with more populations with QTL. This simulation study will help to design biological experiments for detection of QTL-marker association using inbred population and to determine optimum number of lines with fixed QTL during inbred line development. To complement this study, additional simulation should be need with abundant replicates, more various population sizes, magnitude of QTL effects, and recombination between markers and QTLs.

Numerical investigation on effects of rotor control strategy and wind data on optimal wind turbine blade shape

  • Yi, Jin-Hak;Yoon, Gil-Lim;Li, Ye
    • Wind and Structures
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    • v.18 no.2
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    • pp.195-213
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    • 2014
  • Recently, the horizontal axis rotor performance optimizer (HARP_Opt) tool was developed in the National Renewable Energy Laboratory, USA. This innovative tool is becoming more popular in the wind turbine industry and in the field of academic research. HARP_Optwas developed on the basis of two fundamental modules, namely, WT_Perf, a performance evaluator computer code using the blade element momentum theory; and a genetic algorithm module, which is used as an optimizer. A pattern search algorithm was more recently incorporated to enhance the optimization capability, especially the calculation time and consistency of the solutions. The blade optimization is an aspect that is highly dependent on experience and requires significant consideration on rotor control strategies, wind data, and generator type. In this study, the effects of rotor control strategies including fixed speed and fixed pitch, variable speed and fixed pitch, fixed speed and variable pitch, and variable speed and variable pitch algorithms on optimal blade shapes and rotor performance are investigated using optimized blade designs. The effects of environmental wind data and the objective functions used for optimization are also quantitatively evaluated using the HARP_Opt tool. Performance indices such as annual energy production, thrust, torque, and roof-flap moment forces are compared.

An Empirical Study of Port SOC Impact on Trade Volume : Focusing on Japanese Ports (항만 SOC가 수출입에 미치는 영향 실증분석 - 일본 항만을 중심으로 -)

  • Ahn, Young-Gyun;Lee, Joo-Won
    • Korea Trade Review
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    • v.41 no.5
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    • pp.373-389
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    • 2016
  • This study mainly investigates the port SOC's impact on trade volume. In order to investigate the relationships between port SOC and trade volume, we did the empirical analysis using panel data regression and fixed effects model. The total period of 97 years and 1,082 ports' information were applied to panel data and regression model. According to the results, the coefficients of development of container berth, development of bulk berth, maintenance of port, the jetty facilities like breakwater have positive(+) impact on the dependent variable, the trade volume. Especially, the jetty facilities show a strongly positive impact on trade volume. On the other hand, the development of new port and navigation facilities like lighthouse have a negative(-) impact. In examining Hausman test and LR test, the fixed effect model is statistically more appropriate than the random effect model for this study.

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Bayesian Modeling of Random Effects Covariance Matrix for Generalized Linear Mixed Models

  • Lee, Keunbaik
    • Communications for Statistical Applications and Methods
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    • v.20 no.3
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    • pp.235-240
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    • 2013
  • Generalized linear mixed models(GLMMs) are frequently used for the analysis of longitudinal categorical data when the subject-specific effects is of interest. In GLMMs, the structure of the random effects covariance matrix is important for the estimation of fixed effects and to explain subject and time variations. The estimation of the matrix is not simple because of the high dimension and the positive definiteness; subsequently, we practically use the simple structure of the covariance matrix such as AR(1). However, this strong assumption can result in biased estimates of the fixed effects. In this paper, we introduce Bayesian modeling approaches for the random effects covariance matrix using a modified Cholesky decomposition. The modified Cholesky decomposition approach has been used to explain a heterogenous random effects covariance matrix and the subsequent estimated covariance matrix will be positive definite. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using these methods.

Effects of Organic Loading Rates on Treatment Performance in a Polyvinylidene Media Based Fixed-Film Bioreactor

  • Ahmed, Zubair;Oh, Sang-Eun;Kim, In S.
    • Environmental Engineering Research
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    • v.14 no.4
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    • pp.238-242
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    • 2009
  • This study investigated the effects of organic loading rates on simultaneous carbon and nitrogen removal in an innovative fixed-film aerobic bioreactor. The fixed-film bioreactor (FFB) was composed of a two-compartment aeration tank, in which a synthetic filamentous carrier was submerged as biofilm support media, and a settling tank which polyvinylidene media (Saran) was used as settling aid for suspended solids. Three different organic loading rates, ranging from 0.92-2.02 kg chemical oxygen demand/$m^3$/day were applied by varying hydraulic retention time (HRT). The total soluble organic carbon removal efficiencies were in the range of 90-97%. The removal efficiency of ammonia was found to be in the range of 70-84%. Total nitrogen removal efficiency was found to be in the range of 40-45%, which indicates that denitrification reactions occurred simultaneously in the attached biofilm on the fibrous media in the aeration tank. The settling performance of suspended solids was significantly improved due to the presence of Saran media in the settling compartment, even for a short HRT. The fixed-film aerobic bioreactor used in this study demonstrated efficient treatment efficiency even at higher organic loading rates and at short HRTs.

Hierarchical Bayes Estimators of the Error Variance in Balanced Fixed-Effects Two-Way ANOVA Models

  • Kim, Byung-Hwee;Dong, Kyung-Hwa
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.487-500
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    • 1999
  • We propose a class of hierarchical Bayes estimators of the error variance under the relative squared error loss in balanced fixed-effects two-way analysis of variance models. Also we provide analytic expressions for the risk improvement of the hierarchical Bayes estimators over multiples of the error sum of squares. Using these expressions we identify a subclass of the hierarchical Bayes estimators each member of which dominates the best multiple of the error sum of squares which is known to be minimax. Numerical values of the percentage risk improvement are given in some special cases.

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