Stochastic monotonicity of the MLEs of parameters in exponential simple step-stress models under Type-I and Type-II censoring

In two recent papers by Balakrishnan et al. (J Qual Technol 39:35–47, 2007; Ann Inst Stat Math 61:251–274, 2009), the maximum likelihood estimators [^(q)]₁{\hat{\theta}_{1}} and [^(q)]₂{\hat{\theta}_{2}} of the parameters θ ₁ and θ ₂ have been derived in the framework of exponential simple step-stress models under Type-II and Type-I censoring, respectively. Here, we prove that these estimators are stochastically monotone with respect to θ ₁ and θ ₂, respectively, which has been conjectured in these papers and then utilized to develop exact conditional inference for the parameters θ ₁ and θ ₂. For proving these results, we have established a multivariate stochastic ordering of a particular family of trinomial distributions under truncation, which is also of independent interest.     

When is a Compositional Effect not a Compositional Effect?

The question of compositional effects (that is, the effect of collective properties of a pupil body on the individual members), or Aggregated Group-Level Effects (AGLEs) as the author prefers to call them, has been the subject of considerable controversy. Some authors, e.g. Rutter et al. [Fifteen thousand hours: Secondary Schools and Their Effects on Children. London: Open Books.], Willms [Oxford Review of Education 11(1): 33–41; (1986). American Sociological Review, 51, 224–241.], Bondi [British Educational Research Journal, 17(3), 203-218.], have claimed to find such effects, while on the other hand Mortimore et al. [School Matters: the Junior Years. Wells: Open Books.] and Thomas and Mortimore [Oxford Review of Education 16(2): 137–158.] did not. Others, for example Hauser [1970], have implied that many apparent AGLEs may be spurious, while Gray et al. [Review of Research in Education, 8, 158–193.] have suggested that at least in certain circumstances such apparent effects may arise as a result of inadequate allowance for pre-existing differences. A possible statistical mechanism for this is outlined in the work of Burstein [In R. Dreeben, & J. A. Thomas (Eds.), The Analysis of Educational Productivity. Volume 1: Issues in Microanalysis, Cambridge, MASS: Ballinger, pp. 119–190] on the effect of aggregating the data when a variable is omitted from the model used. This paper suggests another way in which spurious AGLEs can arise. It shows mathematically that even if there are no omitted variables, measurement error in an explanatory variable could give rise to apparent, but spurious, AGLEs, when analysed using a multilevel modelling procedure. Using simulation methods, it investigates what the practical effects of this are likely to be, and shows that statistically significant spurious effects occur systematically under fairly standard conditions.     

Estimating a restricted normal mean

Let X ₁, X ₂, ..., X _n be a random sample from a normal distribution with unknown mean μ and known variance σ ². In many practical situations, μ is known a priori to be restricted to a bounded interval, say [−m, m] for some m > 0. The sample mean , then, becomes an inadmissible estimator for μ. It is also not minimax with respect to the squared error loss function. Minimax and other estimators for this problem have been studied by Casella and Strawderman (Ann Stat 9:870–878, 1981), Bickel (Ann Stat 9:1301–1309, 1981) and Gatsonis et al. (Stat Prob Lett 6:21–30, 1987) etc. In this paper, we obtain some new estimators for μ. The case when the variance σ ² is unknown is also studied and various estimators for μ are proposed. Risk performance of all estimators is numerically compared for both the cases when σ ² may be known and unknown.     

A conceptual model of public sector corporate entrepreneurship

Entrepreneurship has been conceptualized as a process that can occur in organizations of all sizes and types (Burgelman, Academy of Management Review, 8, 32–47, 1983; Miller, Management Science, 29, 770–791, 1983; Gartner, Academy of Management Review, 10, 696–706, 1985; Kao, Entrepreneurship, creativity and organization, 1989). This paper develops a conceptual model of public sector corporate entrepreneurship. The proposed model is intended to depict the main antecedents that relate to corporate entrepreneurship within the public sector and the impact of corporate entrepreneurship on public sector organizational performance (growth, development and productivity), as well as factors influencing its continuous performance. Following discussion of the model’s contents, the potential value for researchers and those engaging in public sector corporate entrepreneurship are described.     

On kalman filtering,posterior mode estimation and fisher scoring in dynamic exponential family regression

Summary Dynamic exponential family regression provides a framework for nonlinear regression analysis with time dependent parametersβ ₀,β ₁, …,β _t, …, dimβ _t=p. In addition to the familiar conditionally Gaussian model, it covers e.g. models for categorical or counted responses. Parameters can be estimated by extended Kalman filtering and smoothing. In this paper, further algorithms are presented. They are derived from posterior mode estimation of the whole parameter vector (β′₀, …,β′_t) by Gauss-Newton resp. Fisher scoring iterations. Factorizing the information matrix into block-bidiagonal matrices, algorithms can be given in a forward-backward recursive form where only inverses of “small”p×p-matrices occur. Approximate error covariance matrices are obtained by an inversion formula for the information matrix, which is explicit up top×p-matrices. Heinz Leo Kaufmann, my friend and coauthor for many years, died in a tragical rock climbing accident in August 1989. This paper is dedicated to his memory.     

Determinants of Economic Interaction: Behavior or Structure

Experimental economics originated as examination of the behavior of aggregate phenomena, especially markets, populated by human participants motivated by their desire to attain their goals. The past two decades have brought two newer trends. One is a gradual but steady shift in the focus of the questions sought to be addressed through human experiments towards examination of micro level phenomena – individual preferences and behavior. The second is the expansion in the role of computer simulations to examine questions about aggregate level phenomena. This shift to individual behavior has accentuated the ever-present dilemma of social sciences in trying to be a science on one hand, and to understand our own self-conscious selves – human beings – on the other. To address this dilemma, it would be useful to recognize three streams of experimental economics: (1) macro stream to examine the properties of social structures, (2) micro stream to examine the behavior of individuals, and (3) agent stream to explore the links between the micro and macro phenomena using computer simulations. At least the structural stream can be firmly rooted in the tradition of sciences (bypassing the free-will dilemma of social sciences), while the agent stream can span the gap between the behavioral and structural streams.The author is thankful to Dorota Dobija and Juergen Huber for their helpful comments. Science does not know its debt to imagination. – Ralph Waldo Emerson Vivisection is a social evil because if it advances human knowledge, it does so at the expense of human character. – George Bernard Shaw The theoretical broadening which comes from having many humanities subjects on the campus is offset by the general dopiness of the people who study these things. – Richard P. Feynman Economics has an amazing capacity to summarize staggeringly complex phenomena by the application of only a handful of principles. – Charles R. Plott Being outside and above individual and local contingencies, collective consciousness sees things only in their permanent and fundamental aspects, which it crystallizes in ideas that can be communicated. – Emile Durkheim     

Multivariate likelihood ratio orderings between spacings of heterogeneous exponential random variables

Let X ₁, X ₂, ..., X _n be independent exponential random variables such that X _i has failure rate λ for i = 1, ..., p and X _j has failure rate λ^* for j = p + 1, ..., n, where p ≥ 1 and q = n − p ≥ 1. Denote by D _i:n (p,q) = X _i:n −X _i-1:n the ith spacing of the order statistics X _1:n ≤ X _2:n ≤ ... ≤ X _n:n , i = 1, ..., n, where X _0:n ≡ 0. The purpose of this paper is to investigate multivariate likelihood ratio orderings between spacings D _i:n (p,q), generalizing univariate comparison results in Wen et al.(J Multivariate Anal 98:743–756, 2007). We also point out that such multivariate likelihood ratio orderings do not hold for order statistics instead of spacings. Supported by National Natural Science Foundation of China, the Program for New Century Excellent Talents in University (No.: NCET-04-0569), and by the Knowledge Innovation Program of the Chinese Academy of Sciences (No.: KJCX3-SYW-S02).     

Linearity of regression for non-adjacent order statistics

Let X ₁,X ₂,…,X _n be a random sample from a continuous distribution with the corresponding order statistics X _1:n≤X _2:n≤…≤X _n:n. All the distributions for which E(X _{k+r: n}|X _k:n)=a X _k:n+b are identified, which solves the problem stated in Ferguson (1967). Received February 1998     

A Q-Analysis of Census Data: Intra-Household Income Allocation and School Attendance in Chiapas, Mexico

Q-analysis, introduced by a mathematician Ron Atkin, is a useful tool to explore social structures. I introduce essential concepts and techniques of q-analysis to show q-analysis’s potential ability to analyze and extract information from census data – the work that most researchers have done mainly with statistical methods. Using Mexican census and q-analysis, I examine whether children of female-headed household aged 15–19 were more likely to attend school than male-headed household children in Chiapas, Mexico in 2000. My findings are consistent with the large body of previous research, many of which were conducted with statistical methods: women’s control of income tends to results in a better welfare for their children, defined as children’s school attendance by the sex of heads of household in my study. I evaluate the advantages and disadvantages of a-analysis of census data. I conclude that while it has some weaknesses, q-analysis is a complimentary method to statistical methods for analysis of census data that may overcome some limitations that statistical methods often face such as an incapability of handling a small sample.     

A view on Bhattacharyya bounds for inverse Gaussian distributions

Shanbhag (J Appl Probab 9:580–587, 1972; Theory Probab Appl 24:430–433, 1979) showed that the diagonality of the Bhattacharyya matrix characterizes the set of Normal, Poisson, Binomial, negative Binomial, Gamma or Meixner hypergeometric distributions. In this note, using Shanbhag (J Appl Probab 9:580–587, 1972; Theory Probab Appl 24:430–433, 1979) and Pommeret (J Multivar Anal 63:105–118, 1997) techniques, we evaluated the general form of the 5 × 5 Bhattacharyya matrix in the natural exponential family satisfying f(x|q)=\fracexp{xg(q)}b(g(q))y(x){f(x|\theta)=\frac{\exp\{xg(\theta)\}}{\beta(g(\theta))}\psi(x)} with cubic variance function (NEF-CVF) of θ. We see that the matrix is not diagonal like distribution with quadratic variance function and has off-diagonal elements. In addition, we calculate the 5 × 5 Bhattacharyya matrix for inverse Gaussian distribution and evaluated different Bhattacharyya bounds for the variance of estimator of the failure rate, coefficient of variation, mode and moment generating function due to inverse Gaussian distribution.     

Mixture sets on finite domains

Mixture sets were introduced by Herstein and Milnor (Econometrica 21:291–297, 1953) to prove a generalised expected utility theorem. Mixture sets provide an axiomatisation of convexity suitable for discrete, as well as continuous, environments (Mongin in Decis Econ Finance 24:59–69, 2001). However, the nature of mixture sets over finite domains has been little studied. In this paper, we provide a complete characterisation. More recently, another abstract convex structure for finite domains, the antimatroid, has appeared in the literature on decision theory and social choice. The relationship between mixture sets and antimatroids has not previously been explored. We show here that neither concept is a special case of the other.     

Control Charts for One-sided Capability Indices

There are many industrial product characteristics are desired to be the bigger the best and the smaller the best. The two well-know processes capability indices C _pl and C _pu, which measure larger-the-better and smaller-the-better process capabilities. Obviously, the formulae for the two indices C _pl and C _pu are easy to understand and straightforward to apply. Thus, indices C _pl and C _pu have been utilized by a number of Japanese companies and the U.S. automotive industry by Ford Motor Company. Boyles (1991, Journal of Quality Technology. 23: 17–26) and Spring (1995, Total Quality Management 6(3): 427–438.) point out that as soon as and S control charts are in statistical control, the control charts of process capability indices can be used to monitor the quality of process. In the previous, we know that if the process is not in control, the process capability index control chart can be used to monitor the differences of process capability, and as soon as the process is in control the stable process capability can be identified. Therefore, process capability index control chart not only can be used to monitor the stability of process’s quality but also can be used to monitor the quality of process. Since Boyles (1991, Journal of Quality Technology 23: 17–26.) and Spiring (1995, Total Quality Management 6(1): 21–33.) had had research about control chart of the bilateral specification index C _pm., but there are many kinds of products, which meet unilateral quality specification. Therefore, we will construct the control chart of unilateral specification index C _pl and C _pu to monitor and evaluate the stability of process and process capability.     

Using Clinical Trials to Benchmark Effects Produced in Clinical Practice

This paper proposes an intuitive yet statistical advancement of the benchmarking method (e.g., Weersing and Weisz, 2002, Journal of Consulting and Clinical Psychology 70: 299–310) that could facilitate the assessment of pre-post treatment effectiveness of psychotherapy and other interventions delivered in clinical settings against efficacy observed in clinical trials. Primary development was in the use of the “good-enough principle” (Serlin and Lapsley, 1985 American Psychologist 40: 73–13, 1993, In: G. Keren & C. Lewis (eds.), A handbook for Data Analysis in Behavioral Sciences: Methodological Issues. Hillsdale, NJ: Lawrence Erlbaum Associated, pp. 199–228), which allowed for setting a clinically relevant margin between the benchmarks and the effect sizes observed in clinical settings so as to avoid attaining statistical significance with clinically trivial differences. Examples are given using clinical trials benchmarks of adult depression treatment, followed by instructions and limitations for its use.     

Minimax estimators andΓ-minimax estimators for a bounded normal mean under the lossl p (θ, d)=|θ-d|p

Summary Let the random variableX be normal distributed with known varianceσ ²>0. It is supposed that the unknown meanθ is an element of a bounded intervalΘ. The problem of estimatingθ under the loss functionl _p (θ, d)=|θ-d| ^p p≥2 is considered. In case the length of the intervalθ is sufficiently small the minimax estimator and theΓ(β, τ)-minimax estimator, whereΓ(β, τ) represents special vague prior information, are given.     

Determination of uniformly most powerful tests in discrete sample spaces

Uniformly most powerful (UMP) tests are known to exist in one-parameter exponential families when the hypothesis H ₀ and the alternative hypothesis H ₁ are given by (i) H ₀ : θ≤θ₀, H ₁ : θ>θ₀, and (ii) H ₀ : θ≤θ₁ or θ≥θ₂, H ₁ : θ₁<θ<θ₂, where θ₁<θ₂.  Likewise, uniformly most powerful unbiased (UMPU) tests do exist when the hypotheses H ₀ and H ₁ take the form (iii) H ₀ : θ₁≤θ≤θ₂, H ₁ : θ<θ₁ or θ>θ₂, where θ₁<θ₂, and (iv) H ₀ : θ=θ₀, H ₁:θ≠θ₀.  To determine tests in case (i), only one critical value c and one randomization constant γ have to be computed. In cases (ii) through (iv) tests are determined by two critical values c ₁, c ₂ and two randomization constants γ₁, γ₂. Unlike determination of tests in case (i), computation of critical values and randomization constants in the remaining cases is rather difficult, unless distributions are symmetric. No straightforward method to determine two-sided UMP tests in discrete sample spaces seems to be known. The purpose of this note is to disclose a distribution independent principle for the determination of UMP tests in cases (ii) through (iv). Received: March 1999     

Response of double-auction markets to instantaneous Selling�CBuying signals with stochastic Bid�CAsk spread

Statistical properties of order-driven double-auction markets with Bid–Ask spread are investigated through the dynamical quantities such as response function. We first attempt to utilize the so-called Madhavan–Richardson–Roomans model (MRR for short) to simulate the stochastic process of the price-change in empirical data sets (say, EUR/JPY or USD/JPY exchange rates) in which the Bid–Ask spread fluctuates in time. We find that the MRR theory apparently fails to simulate so much as the qualitative behaviour (‘non-monotonic’ behaviour) of the response function R(l) (l denotes the difference of times at which the response function is evaluated) calculated from the data. Especially, we confirm that the stochastic nature of the Bid–Ask spread causes apparent deviations from a linear relationship between the R(l) and the auto-correlation function C(l), namely, R(l) μ -C(l){R(l) \propto -C(l)}. To make the microscopic model of double-auction markets having stochastic Bid–Ask spread, we use the minority game with a finite market history length and find numerically that appropriate extension of the game shows quite similar behaviour of the response function to the empirical evidence. We also reveal that the minority game modeling with the adaptive (‘annealed’) look-up table reproduces the non-linear relationship R(l) μ -f(C(l)){R(l) \propto -f(C(l))} (f(x) stands for a non-linear function leading to ‘λ-shapes’) more effectively than the fixed (‘quenched’) look-up table does.     

Prediction of <Emphasis Type="Italic">k</Emphasis>-records from a general class of distributions under balanced type loss functions

We study the problem of predicting future k-records based on k-record data for a large class of distributions, which includes several well-known distributions such as: Exponential, Weibull (one parameter), Pareto, Burr type XII, among others. With both Bayesian and non-Bayesian approaches being investigated here, we pay more attention to Bayesian predictors under balanced type loss functions as introduced by Jafari Jozani et al. (Stat Probab Lett 76:773–780, 2006a). The results are presented under the balanced versions of some well-known loss functions, namely squared error loss, Varian’s linear-exponential loss and absolute error loss or L ₁ loss functions. Some of the previous results in the literatures such as Ahmadi et al. (Commun Stat Theory Methods 34:795–805, 2005), and Raqab et al. (Statistics 41:105–108, 2007) can be achieved as special cases of our results. Partial support from Ordered and Spatial Data Center of Excellence of Ferdowsi University of Mashhad is acknowledged by J. Ahmadi. M. J. Jozani’s research supported partially by a grant of Statistical Research and Training Center. é. Marchand’s research supported by NSERC of Canada. A. Parsian’s research supported by a grant of the Research Council of the University of Tehran.     

Determining of threat perceptions affecting direction of the US defense expenditures by using ordinal regression models

The article examines whether the US threat perceptions defined in terms of federal government national defense outlays in billions of constant (FY 2000) dollars change along with periodical changes in international politics between 1945 and 2007. Three different models affecting direction of the US defense expenditures are developed. The first model are estimated by using five link functions even though results of only two of them, complementary log–log and cauchit, are presented. As complementary log–log produced the best results, others models are predicted by using only this function. The parameter estimates of complementary log–log function for the first model indicate that four of these variables (Ford, Carter, Reagan and Bush Sr.) out of eleven are significant in the category of presidents. “Truman Docrtrine/Cominform”, “Korean War”, “Vietnam War”, and “Invasion of Iraq” also seem to be the important independent variables on empirical grounds for the first model. While “Party”, “Invasion of Iraq”, “Vietnam War”, “Korean War”, and “Cuban Missile Crisis” constitute the important independent variables on empirical grounds for the second model, “Korean War”, “Vietnam War”, “Invasion of Iraq”, “Truman Docrtrine/Cominform”, “The Cold War and New World Order”, and “Cuban Missile Crisis” are important independent variables on empirical grounds for the third model. Estimations based on these three models therefore suggest that aforementioned independent variables do indeed have effect on the US defense expenditures.     

Durbin’s random substitution and conditional Monte Carlo

Durbin (Biometrika 48:41–55, 1961) proposed a method called random substitution, by which a composite problem of goodness-of-fit can be reduced to a simple one. In this paper we provide a method of finding the p-value of any test statistic, for a composite goodness-of-fit problem, based on the simulation of a large number of conditional samples, using an analog of Durbin’s proposal in a reverse-type application. We analyze a Bayesian chi-square test proposed in Johnson (Ann Stat 32:2361–2384, 2004) which relies on a single randomization and relate it with Durbin’s original method. We also review a related proposal for conditional Monte-Carlo simulation in Lindqvist and Taraldsen (Biometrika 92:451–464, 2005) and compare it with our procedure. We show our method in a non-group example introduced in Lindqvist and Taraldsen (Biometrika 90:489–490, 2003).     

A note on the maximum deviation of the scale-contaminated normal to the best normal distribution

In this paper we consider the case of the scale-contaminated normal (mixture of two normals with equal mean components but different component variances: (1−p)N(μ,σ²)+pN(μ,τ²) with σ and τ being non-negative and 0≤p≤1). Here is the scale error and p denotes the amount with which this error occurs. It's maximum deviation to the best normal distribution is studied and shown to be montone increasing with increasing scale error. A closed-form expression is derived for the proportion which maximizes the maximum deviation of the mixture of normals to the best normal distribution. Implications to power studies of tests for normality are pointed out. Received May 2001