Forecasting accuracy of behavioural models for participation in the arts

This paper assesses the forecasting performance of count data models applied to arts attendance. We estimate participation models for two artistic activities that differ in their degree of popularity – museums and jazz concerts – with data derived from the 2002 release of the Survey of Public Participation in the Arts for the United States. We estimate a finite mixture model – a zero-inflated negative binomial model – that allows us to distinguish between “true” non-attendants and “goers” and their respective behaviour regarding participation in the arts. We evaluate the predictive (in-sample) and forecasting (out-of-sample) accuracy of the estimated model using bootstrapping techniques to compute the Brier score. Overall, the results indicate the model performs well in terms of forecasting. Finally, we draw certain policy implications from the model’s forecasting capacity, thereby allowing the identification of target populations.     

m相依样本均值的Bootstrap及其随机加权逼近的收敛速度

本文研究了ｍ相依样本均值的Ｂｏｏｔｓｔｒａｐ及随机加权逼近问题，讨论了有关收敛速度。     

Parallel and bootstrapped stochastic approximation

Parallelization of stochastic approximation procedures can reduce computation and total observation time of a system. Concerning the number of all observations used by the pure sequential and the suggested parallel method a weak invariance principle implies the asymptotic equivalence of both methods. A loglog invariance principle and a rate of a.s. convergence result describe the pathwise properties. Due to the parallel design asymptotic confidence regions can readily be constructed either by computing the bootstrap distribution or the Gaussian limit distribution determined by the empirical covariance     

Premium rates based on genetic studies: How reliable are they?

Underwriting the risk of rare disorders in long-term insurance often relies on rates of onset estimated from quite small epidemiological studies. These estimates can have considerable sampling uncertainty and any function based upon them, such as a premium rate, is also an estimate subject to uncertainty. This is particularly relevant in the case of genetic disorders, because the acceptable use of genetic information may depend on establishing its reliability as a measure of risk. The sampling distribution of a premium rate is hard to estimate without access to the original data, which is rarely possible. From two studies of adult polycystic kidney disease (APKD) we obtain, not the original data, but the cases and exposures used for Kaplan-Meier estimates of the survival probability. We use three resampling methods with these data, namely: (a) the standard bootstrap; (b) the weird bootstrap; and (c) simulation of censored random lifetimes. Rates of onset were obtained from each simulated sample using kernel-smoothed Nelson-Aalen estimates, hence critical illness insurance premium rates for a mutation carrier or a member of an affected family. From 10,000 such samples we estimate the sampling distributions of the premium rates, finding considerable uncertainty. Very careful consideration should be given before using small-sample epidemiological data to deal with insurance problems.     

Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping

This paper proposes a novel method to select an experimental design for interpolation in random simulation, especially discrete event simulation. (Though the paper focuses on Kriging, this design approach may also apply to other types of metamodels such as non-linear regression models and splines.) Assuming that simulation requires much computer time, it is important to select a design with a small number of observations (or simulation runs). The proposed method is therefore sequential. Its novelty is that it accounts for the specific input/output behavior (or response function) of the particular simulation at hand; i.e., the method is customized or application-driven. A tool for this customization is bootstrapping, which enables the estimation of the variances of predictions for inputs not yet simulated. The method is tested through two classic simulation models, namely the expected steady-state waiting time of the M/M/1 queuing model, and the mean costs of a terminating (s, S) inventory simulation. For these two simulation models the novel design indeed gives better results than a popular alternative design, namely Latin Hypercube Sampling (LHS) with a prefixed sample.     

Use of the bootstrap and permutation methods for a more robust variable importance in the projection metric for partial least squares regression

Bio-pharmaceutical manufacturing is a multifaceted and complex process wherein the manufacture of a single batch hundreds of processing variables and raw materials are monitored. In these processes, identifying the candidate variables responsible for any changes in process performance can prove to be extremely challenging. Within this context, partial least squares (PLS) has proven to be an important tool in helping determine the root cause for changes in biological performance, such as cellular growth or viral propagation. In spite of the positive impact PLS has had in helping understand bio-pharmaceutical process data, the high variability in measured response (Y) and predictor variables (X), and weak relationship between X and Y, has at times made root cause determination for process changes difficult. Our goal is to demonstrate how the use of bootstrapping, in conjunction with permutation tests, can provide avenues for improving the selection of variables responsible for manufacturing process changes via the variable importance in the projection (PLS-VIP) statistic. Although applied uniquely to the PLS-VIP in this article, the generality of the aforementioned methods can be used to improve other variable selection methods, in addition to increasing confidence around other estimates obtained from a PLS model.     

Calibrating affine stochastic mortality models using term assurance premiums

In this paper, we focus on the calibration of affine stochastic mortality models using term assurance premiums. We view term assurance contracts as a “swap” in which policyholders exchange cash flows (premiums vs. benefits) with an insurer analogous to a generic interest rate swap or credit default swap. Using a simple bootstrapping procedure, we derive the term structure of mortality rates from a stream of contract quotes with different maturities. This term structure is used to calibrate the parameters of affine stochastic mortality models where the survival probability is expressed in closed form. The Vasicek, Cox-Ingersoll-Ross, and jump-extended Vasicek models are considered for fitting the survival probabilities term structure. An evaluation of the performance of these models is provided with respect to premiums of three Italian insurance companies.     

基于密度泛函理论与自举软缩减法的酒石酸太赫兹光谱特征谱区分析指认

太赫兹时域光谱不但包含了样品的化学信息和物理信息,还承载了设备噪声、样品状态、环境参数等多方面的背景信息,其光谱的多元性可能影响模型的性能,降低预测精度。能否在复杂、重叠、变动背景下从光谱数据中提取目标组分的特征信息,去除冗余变量,筛选特征谱区,对太赫兹光谱定量、定性分析至关重要。以L-酒石酸为研究对象,在室温下采集6个浓度：10%,20%,40%,50%,60%和80%,共计342个样本的L-酒石酸太赫兹吸收光谱。利用密度泛函理论(DFT)中的B3LYP方法,基于6-31G*(d,p)基组对L-酒石酸单分子模型进行优化并对其太赫兹频谱特性进行理论模拟计算,分析对应特征波峰的分子振动模式,得到0.2～1.6 THz频段吸收谱。与实测吸收谱进行对比,实验所测结果与理论计算结果对应的吸收峰位置基本吻合。采用自举软缩减法（BOSS）对L-酒石酸的太赫兹吸收谱进行特征谱区筛选,并与竞争性自适应加权采样（CARS）、蒙特卡洛无信息变量消除法（MC-UVE）和间隔区间偏最小二乘法（iPLS）3种经典特征谱区筛选法进行对比,分析结果显示BOSS算法选取的有效谱区与DFT理论计算特征谱区重合度最优。分别使用全谱PLS,CARS-PLS,MC-UVE-PLS,iPLS及BOSS五种算法对L-酒石酸光谱进行建模回归分析,实验结果表明,四种谱区筛选方法相较于全谱PLS模型,预测精度均有所提高,其中BOSS算法预测能力提高最为显著,其交互验证均方根误差（RMSECV）、预测均方根误差（RMSEP）、训练集决定系数(R2_train)和测试集决定系数(R2_test)分别为0.026 0,0.026 0,0.988 1和0.987 5,相较其他模型有更高的预测精度和模型稳定性,为实现基于太赫兹光谱技术的快速定量检测提供了一种有效的方法。     

Multifractality in stock indexes: Fact or Fiction?

Multifractal analysis and extensive statistical tests are performed upon intraday minutely data within individual trading days for four stock market indexes (including HSI, SZSC, S&P 500, and NASDAQ) to check whether the indexes (instead of the returns) possess multifractality. We find that the mass exponent τ(q) is linear and the singularity α(q) is close to 1 for all trading days and all indexes. Furthermore, we find strong evidence showing that the scaling behaviors of the original data sets cannot be distinguished from those of shuffled time series. Hence, the so-called multifractality in the intraday stock market indexes is merely an illusion.     

Measuring the efficiency of highway maintenance contracting strategies: A bootstrapped non-parametric meta-frontier approach

Highly deteriorated US road infrastructure, major budgetary restrictions and the significant growth in traffic have led to an emerging need for improving performance of highway maintenance practices. Privatizing some portions of road maintenance operations by state Departments of Transportation (DOTs) under the auspices of performance-based contracts has been one of the innovative initiatives in response to such a need. This paper adapts the non-parametric meta-frontier framework to the two-stage bootstrapping technique to develop an analytical approach for evaluating the relative efficiency of two highway maintenance contracting strategies. The first strategy pertains to the 180 miles of Virginia’s Interstate highways maintained by Virginia DOT using traditional maintenance practices. The second strategy pertains to the 250 miles of Virginia’s Interstate highways maintained via a Public Private Partnership using a performance-based maintenance approach. The meta-frontier approach accounts for the heterogeneity that exists among different types of highway maintenance contracts due to different limitations and regulations. The two-stage bootstrapping technique accounts for the large set of uncontrollable factors that affect the highway deterioration processes. The preliminary findings, based on the historical data for the state of Virginia, suggest that road authorities (counties) that have used traditional contracting for transforming the maintenance expenditures into the improvement of the road conditions seem to be more efficient than road authorities that have used the performance-based contracting. This paper recommends that road authorities use hybrid contracting approaches that include best practices of both traditional and performance-based highway maintenance contracting.