Sample size and the Binomial CUSUM Control Chart: the case of 100% inspection

The Binomial CUSUM is used to monitor the fraction defective (p) of a repetitive process, particularly for detecting small to moderate shifts. The number of defectives from each sample is used to update the monitoring CUSUM. When 100% inspection is in progress, the question arises as to how many sequential observations should be grouped together in forming successive samples. The tabular form of the CUSUM has three parameters: the sample size n, the reference value k, and the decision interval h, and these parameters are usually chosen using statistical or economic-statistical criteria, which are based on Average Run Length (ARL). Unlike earlier studies, this investigation uses steady-state ARL rather than zero-state ARL, and the occurrence of the shift can be anywhere within a sample. The principal finding is that there is a significant gain in the performance of the CUSUM when the sample size (n) is set at one, and this CUSUM might be termed the Bernoulli CUSUM. The advantage of using n=1 is greater for larger shifts and for smaller values of in-control ARL. First version: September 1998/Third revision: September 2000     

广义Lucas数列的一些求和公式

由二次线性递推公式所定义的Lucas数列ΣLnΣ在数学的理论研究中有重要的作用.本文在已有的有关广义Lucas数列相关定理的基础上进一步推广,给出了更为广泛的广义Lucas数列的求和公式,采用了递推归纳的方法证明。     

Performance monitoring of credit portfolios using survival analysis

We are interested in detecting changes in the performance of a credit portfolio quickly and robustly. The portfolio is dynamic: customers can either default or pay the full amount, and new customers can be taken on. Robust detection means that changing the number of new customers taken on should not lead to either a false or delayed signal. We investigate the performances of monitoring schemes via a simulation study that uses several scenarios. We consider monitoring based on default rates estimated through a gliding window, cumulative sum (CUSUM) charts based on default rates, CUSUM charts based on defaults within a given follow-up time after arrival, and a survival analysis CUSUM chart. We conclude that using a survival analysis approach is preferable to using the other approaches.     

A non-local perspective on the power properties of the CUSUM and CUSUM of squares tests for structural change

We consider the power properties of the CUSUM and CUSUM of squares (CUSQ) tests in the presence of a one-time change in the parameters of a linear regression model. A result due to Ploberger and Krämer [1990. The local power of the cusum and cusum of squares tests. Econometric Theory 6, 335–347.] is that the CUSQ test has only trivial asymptotic local power in this case, while the CUSUM test has non-trivial local asymptotic power unless the change is orthogonal to the mean regressor. The main theme of the paper is that such conclusions obtained from a local asymptotic framework are not reliable guides to what happens in finite samples. The approach we take is to derive expansions of the test statistics that retain terms related to the magnitude of the change under the alternative hypothesis. This enables us to analyze what happens for non-local to zero breaks. Our theoretical results are able to explain how the power function of the tests can be drastically different depending on whether one deals with a static regression with uncorrelated errors, a static regression with correlated errors, a dynamic regression with lagged dependent variables, or whether a correction for non-normality is applied in the case of the CUSQ. We discuss in which cases the tests are subject to a non-monotonic power function that goes to zero as the magnitude of the change increases, and uncover some curious properties. All theoretical results are verified to yield good guides to the finite sample power through simulation experiments. We finally highlight the practical importance of our results.     

Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels

Stationary bootstrapping is applied to a CUSUM test for common mean break detection in cross-sectionally correlated panel data. Asymptotic null distribution of the bootstrapped test is derived, which is the same as that of the original CUSUM test depending on cross-sectional correlation parameter. A bootstrap test using the CUSUM test with bootstrap critical values is proposed and its asymptotic validity is proved. Finite sample Monte-Carlo simulation shows that the proposed test has reasonable size while other existing tests have severe size distortion under cross-section correlation. The simulation also shows good power performance of the proposed test against non-cancelling mean changes. The simulation also shows that the theoretically justified stationary bootstrapping CUSUM test has comparable size and power relative to other, theoretically unjustified, moving block or tapered block bootstrapping CUSUM tests.     

The dynamics of regional inequalities

This paper analyses the link between regional inequalities and GDP per capita at the country-level. Our starting hypothesis is that the evolution of regional inequalities should follow a bell-shaped curve as national GDP per capita rises since growth by its very nature is unlikely to appear everywhere at the same time, as has been argued by a number of authors, from Kuznets [Kuznets, S., (1955), Economic growth and income inequality, American Economic Review 45(1), 1–28] to Lucas [Lucas, R.E., (2000), “Some macroeconomics for the 21st century”, Journal of Economic Perspectives 14 (1), 159–168]. We test this hypothesis econometrically using semi-parametric estimation techniques and regional data for a panel of European countries. Our results provide strong support for such a bell-shaped curve and are robust to changing the regional administrative units and the time period, as well as controlling for other possible determinants of regional inequalities. We also find support for this hypothesis when considering non-European countries.     

Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

Surveillance of the mean behavior of multivariate time series

In this paper several cumulative sum (CUSUM) charts for the mean of a multivariate time series are introduced. We extend the control schemes for independent multivariate observations of crosier [ Technometrics (1988) Vol. 30, pp. 187–194], pignatiello and runger [ Journal of Quality Technology (1990) Vol. 22, pp. 173–186], and ngai and zhang [ Statistica Sinica (2001) Vol. 11, pp. 747–766] to multivariate time series by taking into account the probability structure of the underlying stochastic process. We consider modified charts and residual schemes as well. It is analyzed under which conditions these charts are directionally invariant. In an extensive Monte Carlo study these charts are compared with the CUSUM scheme of theodossiu [ Journal of the American Statistical Association (1993) Vol. 88, pp. 441–448], the multivariate exponentially weighted moving-average (EWMA) chart of kramer and schmid [ Sequential Analysis (1997) Vol. 16, pp. 131–154], and the control procedures of bodnar and schmid [ Frontiers of Statistical Process Control (2006) Physica, Heidelberg]. As a measure of the performance, the maximum expected delay is used.     

Steriel of niet steriel, dat is de vraag

Summary  This paper deals with a practical problem of sampling inspection, viz. the bacterial control of imported fishmeal (which is used in food for pigs). It was suspected that this fishmeal was often contaminated by salmonella-bacteria, but only in about 0.5% of the samples the presence of these bacteria could be proved. An investigation by the Dutch National Institute of Public Health, at which 4 bags of fishmeal (about 50 kg) after homogenization were divided into 1000 samples of 50 grams each which were individually tested on the presence of salmonella bacteria, showed that nothwithstanding the homogenization the bacteria were very irregularly distributed. Every bag was contaminated, but only about 1.8% of the samples were infected. So the density of infection was low, but the fraction of infected bags was high.
If the fishmeal were fed in a dry condition to the pigs the relevant parameter on which the condition of the fishmeal should be judged would have been the mean number of bacteria per gram of fishmeal. However, as food for pigs is mixed with water the bacteria have the possibility to increase in number so the relevant parameter to judge a batch of fishmeal is the fraction of non-sterile bags.
At the end of this paper a sampling scheme is given, including a system of penalty for producers who regularly supply contaminated fishmeal which will in a relative short time improve the quality of the imported fishmeal.     

Steriel of niet steriel,dat is de vraag

Summary This paper deals with a practical problem of sampling inspection, viz. the bacterial control of imported fishmeal (which is used in food for pigs). It was suspected that this fishmeal was often contaminated by salmonella-bacteria, but only in about 0.5% of the samples the presence of these bacteria could be proved. An investigation by the Dutch National Institute of Public Health, at which 4 bags of fishmeal (about 50 kg) after homogenization were divided into 1000 samples of 50 grams each which were individually tested on the presence of salmonella bacteria, showed that nothwithstanding the homogenization the bacteria were very irregularly distributed. Every bag was contaminated, but only about 1.8% of the samples were infected. So the density of infection was low, but the fraction of infected bags was high. If the fishmeal were fed in a dry condition to the pigs the relevant parameter on which the condition of the fishmeal should be judged would have been the mean number of bacteria per gram of fishmeal. However, as food for pigs is mixed with water the bacteria have the possibility to increase in number so the relevant parameter to judge a batch of fishmeal is the fraction of non-sterile bags. At the end of this paper a sampling scheme is given, including a system of penalty for producers who regularly supply contaminated fishmeal which will in a relative short time improve the quality of the imported fishmeal.     

Structural evolution of the postwar U.S. economy

We consider a time-varying parameter vector autoregressive model with stochastic volatility and mixture innovations to study the empirical relevance of the Lucas critique for the postwar U.S. economy. The model allows blocks of parameters to change at endogenously estimated points of time. Contrary to the Lucas critique, there are large changes at certain points of time in the parameters associated with monetary policy that do not correspond to changes in “reduced-form” parameters for inflation or the unemployment rate. However, the structure of the U.S. economy has evolved considerably over the postwar period, with an apparent reduction in the late 1980s in the impact of monetary policy shocks on inflation, though not on the unemployment rate. Related, we find changes in the Phillips curve tradeoff between inflation and cyclical unemployment (measured as the deviation from the time-varying steady-state unemployment rate implied by the model) in the 1970s and especially since the mid-1990s.     

The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance*

This article discusses the asymptotic and finite‐sample properties of the CUSUM tests for detecting structural breaks in volatility when the data are perturbed with (additive) outliers and/or measurement errors. The special focus is on the parametric and non‐parametric tests in Inclán and Tiao (1994) and Kokoszka and Leipus (2000) . Whereas the asymptotic distribution of the former can be largely affected, the distribution of the latter remains invariant and renders consistent break‐point estimates. In small samples, however, large additive outliers are able to generate sizeable distortions in both tests, which explains some of the contradictory findings in previous literature.     

Change-point detection for expected shortfall in time series

Expected shortfall (ES) is a popular risk measure and plays an important role in risk and portfolio management. Recently, change-point detection of risk measures has been attracting much attention in finance. Based on the self-normalized CUSUM statistic in Fan, Glynn and Pelger (2018) and the Wild Binary Segmentation (WBS) algorithm in Fryzlewicz (2014), this paper proposes a variant WBS procedure to detect and estimate change points of ES in time series. The strengthened Schwarz information criterion is also introduced to determine the number of change points. Monte Carlo simulation studies are conducted to assess the finite-sample performance of our variant WBS procedure about ES in time series. An empirical application is given to illustrate the usefulness of our procedure.     

Count data stochastic frontier models, with an application to the patents–R&D relationship

This article introduces a new count data stochastic frontier model that researchers can use in order to study efficiency in production when the output variable is a count (so that its conditional distribution is discrete). We discuss parametric and nonparametric estimation of the model, and a Monte Carlo study is presented in order to evaluate the merits and applicability of the new model in small samples. Finally, we use the methods discussed in this article to estimate a production function for the number of patents awarded to a firm given expenditure on R&D.     

Mixture cumulative count control chart for mixture geometric process characteristics

A statistical process control chart named the mixture cumulative count control chart (MCCC-chart) is suggested in this study, motivated by an existing control chart named cumulative count control chart (CCC-chart). The MCCC-chart is constructed based on the distribution function of a two component mixture of geometric distributions using the number of items inspected until a defective item is observed ‘n’ as plotting statistics. We have observed that the MCCC-chart has the ability to perform equivalent to the CCC-chart when number of defective items follows geometric distribution and better than the CCC-chart when the number of defective items produced by a process follows a mixture geometric model. The MCCC-chart may be considered as a generalized version of CCC-chart.     

Growth and the diffusion of ideas

In a recent model of growth developed by Lucas (Lucas, R., 2009. Ideas and growth. Economica 76, 1–19), a continuum of people interact in a random manner and copy each other’s productive ideas when it is economically beneficial to do so. This paper extends the Lucas model by assuming that each person’s productivity also experiences random shocks due to individual discovery. A nonlinear partial differential equation is derived for the distribution of income, which admits a traveling wave solution representing a growing economy. The growth rate is an increasing function of the rate of imitation. The growth rate is also an increasing but concave function of population size and reaches a plateau in the continuum limit. Hence the scale effect is bounded. The model is extended to account for a nonzero cost of imitation, with similar results. The mathematical tools presented in this paper should prove useful in developing idea-based models of growth.     

偏远地区太阳能系统最佳配置的研究

偏远地区电网延伸困难,对于经济不发达的农村,太阳能供电系统是一个优秀的解决方案。文章提出了一种太阳能光伏电池(PV-BAT)系统的最佳配置方案,该方案计算简单,具有高可靠性和低成本的特点。该方法已应用于某一偏僻地区的负载要求的设计,为其提供了一个最佳的光伏系统。     

Models for truncated counts

This paper examines a class of maximum-likelihood regression estimators for count data from truncated samples. Estimators for the truncated Poisson and negative binomial distributions are illustrated. Simulation results are given to illustrate the magnitude of the bias that may result from the failure to account for overdispersion in truncated samples. An empirical application based upon the number of recreational fishing trips taken by a sample of Alaskan fishermen is provided.     

Mitigation of the Lucas critique with stochastic control methods

Lucas (In: Brunner, K., Meltzer, A.H. (Eds.), The Phillips Curve and the Labor Markets, Supplementary Series to the Journal of Monetary Economics, 1976, pp. 19–46) pointed out, that when optimization is performed on a deterministic macro model, the resulting policy may not reflect the true optimal solution. Private agents may react to announced policies and consequently model parameters will start to drift. The aim of this paper is to develop a methodology for deriving an optimal policy in the presence of rational expectations and parameter drift. This drift is captured by a stochastic optimization framework with time-varying parameters. The resulting optimal policy is capable of tracking changes in the parameters due to policy changes. A numerical example illustrates how the methodology provides a way to mitigate the effects of the Lucas critique.     

Powerful tests for structural changes in volatility

Detecting structural changes in volatility is important for understanding volatility dynamics and stylized facts observed for financial returns such as volatility persistence. We propose modified CUSUM and LM tests that are built on a robust estimator of the long-run variance of squared series. We establish conditions under which the new tests have standard null distributions and diverge faster than standard tests under the alternative. The theory allows smooth and abrupt structural changes that can be small. The smoothing parameter is automatically selected such that the proposed test has good finite-sample size and meanwhile achieves decent power gain.