• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.225-237
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• 2024

Purpose - This study aims to explore the relationship between housing and land prices, with a specific emphasis on the impact of government policies on these factors such as land supply quantity and the ratio of residential land to total land supplied. The goal is to identify the most effective government intervention strategies for controlling both housing and land prices. Design/methodology/approach - Data from 70 primary and medium-sized cities in China spanning from 2003 to 2017 are utilized in this research. The analysis employs a panel vector autoregressive (PVAR) model, with a primary focus on examining the relationships among housing prices, land prices, and government intervention policies. Findings - Housing and land prices are influenced by various factors. Through impulse response analysis and variance decomposition, it is observed that both housing and land prices are predominantly influenced by their internal dynamics, with comparatively weaker effects attributed to policy interventions. Research implications or Originality - By investigating the impact of government policies on housing and land prices, This study establishes a foundation for effective price control measures. Our study advocates for a comprehensive examination of China's land supply mechanism to enhance understanding of the pathways through which government policies influence the markets.

• The Journal of Korean Physical Therapy
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• v.31 no.3
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• pp.151-156
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• 2019

Purpose: This study aimed to investigate the immediate effects of posture correction and real-time visual feedback using a video display on muscle activity and change of head position during overhead arm lift test in individuals with forward head posture. Methods: Fifteen subjects with forward head posture and fifteen normal subjects who volunteered were included in this study. During both groups performed the overhead arm lift test, the muscle activity of the upper trapezius, serratus anterior, sternocleidomastoid, and lower trapezius muscle were measured using electromyography, and head position change was measured using photographs. Then, forward head posture group was asked to perform overhead arm lift test again after posture correction and real-time visual feedback using a video display respectively. One-way analysis of variance (ANOVA) was used to analyze four conditions: pre-test, posture correction, real-time visual feedback, and the control group. Results: The upper trapezius and lower trapezius muscle activity significantly decreased posture correction, real-time visual feedback, and control group than pre-test of forward head posture group (p<0.05). The sternocleidomastoid muscle significantly decreased real-time visual feedback and control group than pre-test of forward head posture group. Head position change significantly decreased three conditions than pre-test of forward head posture group and real-time visual feedback and control group significantly decreased than posture correction. Conclusion: This study recommend for maintaining cervical stability during the overhead arm lift test, postural control using real-time visual feedback is more effective in subjects with forward head posture.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.67-72
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• 2002

A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.557-573
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• 2015

In this paper we develop a Bayesian inference for a multiplicative double seasonal autoregressive (DSAR) model by implementing a fast, easy and accurate Gibbs sampling algorithm. We apply the Gibbs sampling to approximate empirically the marginal posterior distributions after showing that the conditional posterior distribution of the model parameters and the variance are multivariate normal and inverse gamma, respectively. The proposed Bayesian methodology is illustrated using simulated examples and real-world time series data.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.11-21
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• 2007

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the difference between two normal means with unknown com-mon variance. We derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We illustrate our results using real data analysis as well as simulation study.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.201-212
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• 2014

We provide a simple basic method to find bounds for higher order moments of unimodal distributions in terms of lower order moments when the random variable takes value in a given finite real interval. The bounds for moments in terms of the geometric mean of the distribution are also derived. Both continuous and discrete cases are considered. The bounds for the ratio and difference of moments are obtained. The special cases provide refinements of several well-known inequalities, such as Kantorovich inequality and Krasnosel'skii and Krein inequality.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.53-62
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• 1994

When a comparison is made with respect to the unknown best treatment, Hsu (1984, 1985) proposed the so called multiple comparisons procedures with the best in the analysis of variance model. Applying Hsu's results to the analysis of covariance model, simultaneous confidence intervals for multiple comparisons with the best in a balanced one-way layout with a random covariate are developed and are applied to a real data example.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.420-427
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• 2004

Increasing number of transactions and investments in technology has sparked a growing interest in technology valuation. However, it has not been easy to come up with an objective valuation of technology due to variance in technology value, purpose of valuation, and technology patterns. The central paradigm for making decisions about large technology investments is net present value. Unfortunately, it is badly flawed and systematically under values every investment opportunity. The main objective of this paper lies in the development of a new approach for technology valuation using the Real Option Valuation.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.151-165
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• 1999

This paper considers the trimmed least squares estimator of the autoregression parameter in the unstable AR(1) model: X\ulcorner=ØX\ulcorner+$\varepsilon$\ulcorner, where $\varepsilon$\ulcorner are iid random variables with mean 0 and variance $\sigma$$^2$> 0, and Ø is the real number with │Ø│=1. The trimmed least squares estimator for Ø is defined in analogy of that of Welsh(1987). The limiting distribution of the trimmed least squares estimator is derived under certain regularity conditions.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.72-76
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• 1990

A new statistical linearization technique for nonlinear system called covariance matching method is proposed in this paper. The covariance matching method makes the mean and variance of an approximated output be identical real functional output, and the distribution of the approximated output have identical shape with a given random input. Also, the covariance matching method can be easily implemented for statistical analysis of nonlinear systems with a combination of linear system covariance analysis.