The longitudinal effects of parental monitoring and self-control on depression in Korean adolescents: A multivariate latent growth approach

The purpose of this study was to examine the longitudinal effects of parental monitoring and self-control on depression. To address this purpose, this study investigated the interrelationships among depression, perceived parental monitoring, and self-control—as well as their developmental changes from the eighth to the twelfth grades—by repeated assessment of 3449 Korean adolescents. The data from Korea Youth Panel Survey (KYPS) of the eighth graders who were followed for five years were analyzed using latent growth modeling. The univariate latent growth models showed that adolescents experience an increase in both parental monitoring and self-control but a decline in depression over the five years. In addition, the multivariate latent growth model suggested that the initial level of parental monitoring had significant effects, both directly and indirectly through self-control, on the initial level of depression. The linear changes in parental monitoring were associated with the linear changes in self-control; likewise, the linear changes in self-control were related to those in depression. These results imply that parental monitoring and self-control need to be emphasized as a strategy in order to prevent or alleviate adolescents' depression.     

The Economic Value of Career Counseling Services for College Students in South Korea

This study investigated college students’ perception of the monetary value of career counseling services by using the contingent valuation method. The results of a multivariate survival analysis based on interviews with a convenience sample of 291 undergraduate students in South Korea indicate that, on average, participants’ expressed willingness to pay (WTP) for such services ranged from U.S. $10.22 to $10.54 per hour of individual career counseling. Self‐stigma and attitudes toward counseling had positive effects on their WTP, whereas the year in college and social stigma had negative effects. The results provide policy makers with preliminary evidence of the monetary value of career counseling.     

$$$$-labeling number of Cartesian product of path and cycle

For positive numbers \(j\) and \(k\), an \(L(j,k)\)-labeling \(f\) of \(G\) is an assignment of numbers to vertices of \(G\) such that \(|f(u)-f(v)|\ge j\) if \(d(u,v)=1\), and \(|f(u)-f(v)|\ge k\) if \(d(u,v)=2\). The span of \(f\) is the difference between the maximum and the minimum numbers assigned by \(f\). The \(L(j,k)\)-labeling number of \(G\), denoted by \(\lambda _{j,k}(G)\), is the minimum span over all \(L(j,k)\)-labelings of \(G\). In this article, we completely determine the \(L(j,k)\)-labeling number (\(2j\le k\)) of the Cartesian product of path and cycle.     

Estimation of finite mixtures with symmetric components

It may sometimes be clear from background knowledge that a population under investigation proportionally consists of a known number of subpopulations, whose distributions belong to the same, yet unknown, family. While a parametric family is commonly used in practice, one can also consider some nonparametric families to avoid distributional misspecification. In this article, we propose a solution using a mixture-based nonparametric family for the component distribution in a finite mixture model as opposed to some recent research that utilizes a kernel-based approach. In particular, we present a semiparametric maximum likelihood estimation procedure for the model parameters and tackle the bandwidth parameter selection problem via some popular means for model selection. Empirical comparisons through simulation studies and three real data sets suggest that estimators based on our mixture-based approach are more efficient than those based on the kernel-based approach, in terms of both parameter estimation and overall density estimation.     

马来班顿体和土生华人班顿体比兴中的自然物象

对某些学者而言,马来班顿体也许是马来世界和马来灵魂的完美镜像。班顿体是一种口头文学,它扎根于许多不同的族群中,通过口头方式代代相传。本文的研究焦点是马来和马来西亚土生华人班顿体,其中有些文本直接录自马六甲和新加坡的口述者,分析的重点是马来班顿体首联中对自然的偏爱是如何在土生华人班顿体中得到强调的。此外,强调自然比兴的这种手法是马来班顿体和土生华人班顿体冲突后产生的“镜像效应”。这两种班顿体中反复出现的自然景象强调了当时与之紧密相关的日常生活,同时也形成了班顿体独特的审美性。     

Testing for spurious and cointegrated regressions: A wavelet approach

This paper proposes a wavelet-based approach to analyze spurious and cointegrated regressions in time series. The approach is based on the properties of the wavelet covariance and correlation in Monte Carlo studies of spurious and cointegrated regression. In the case of the spurious regression, the null hypotheses of zero wavelet covariance and correlation for these series across the scales fail to be rejected. Conversely, these null hypotheses across the scales are rejected for the cointegrated bivariate time series. These nonresidual-based tests are then applied to analyze if any relationship exists between the extraterrestrial phenomenon of sunspots and the earthly economic time series of oil prices. Conventional residual-based tests appear sensitive to the specification in both the cointegrating regression and the lag order in the augmented Dickey–Fuller tests on the residuals. In contrast, the wavelet tests, with their bootstrap t-statistics and confidence intervals, detect the spuriousness of this relationship.     

Notes on L(1,1) and L(2,1) labelings for n-cube

Suppose \(d\) is a positive integer. An \(L(d,1)\) -labeling of a simple graph \(G=(V,E)\) is a function \(f:V\rightarrow \mathbb{N }=\{0,1,2,{\ldots }\}\) such that \(|f(u)-f(v)|\ge d\) if \(d_G(u,v)=1\) ; and \(|f(u)-f(v)|\ge 1\) if \(d_G(u,v)=2\) . The span of an \(L(d,1)\) -labeling \(f\) is the absolute difference between the maximum and minimum labels. The \(L(d,1)\) -labeling number, \(\lambda _d(G)\) , is the minimum of span over all \(L(d,1)\) -labelings of \(G\) . Whittlesey et al. proved that \(\lambda _2(Q_n)\le 2^k+2^{k-q+1}-2,\) where \(n\le 2^k-q\) and \(1\le q\le k+1\) . As a consequence, \(\lambda _2(Q_n)\le 2n\) for \(n\ge 3\) . In particular, \(\lambda _2(Q_{2^k-k-1})\le 2^k-1\) . In this paper, we provide an elementary proof of this bound. Also, we study the \(L(1,1)\) -labeling number of \(Q_n\) . A lower bound on \(\lambda _1(Q_n)\) are provided and \(\lambda _1(Q_{2^k-1})\) are determined.     

ON THE DERIVATION AND COMPUTATION OF THE CORNISH-FISHER EXPANSION

The paper gives a simple derivation based on elementary statistics for the Cornish—Fisher expansion. The method simplifies greatly the algebra in working out the polynomials involved both in the normalization and in the inverse expansions. The derivation also leads to recursive formulae which yield powerful algorithms for numerical computation of the expansion.     

Robust precision matrix estimation via weighted median regression with regularization

A precision matrix is an important parameter of interests because its elements describe useful association information among multiple variables, which has a wide variety of applications. For example, it is used for inferring gene regulation networks in genomic studies and stock association networks in financial studies. However, in many cases, the precision matrix needs to be robustly estimated due to the presence of outliers. We propose estimating a sparse scaled precision matrix via weighted median regression with regularization. Our weighted median regression approach is consistent under various distributional assumptions including multivariate t‐ or contaminated Gaussian distributions. This fact is illustrated with simulation studies and a real data analysis with monthly stock return data. The Canadian Journal of Statistics 46: 265–278; 2018 © 2018 Statistical Society of Canada     

Distance-based outlier detection for high dimension,low sample size data

Despite the popularity of high dimension, low sample size data analysis, there has not been enough attention to the sample integrity issue, in particular, a possibility of outliers in the data. A new outlier detection procedure for data with much larger dimensionality than the sample size is presented. The proposed method is motivated by asymptotic properties of high-dimensional distance measures. Empirical studies suggest that high-dimensional outlier detection is more likely to suffer from a swamping effect rather than a masking effect, thus yields more false positives than false negatives. We compare the proposed approaches with existing methods using simulated data from various population settings. A real data example is presented with a consideration on the implication of found outliers.