On the detection of changes in autoregressive time series I. Asymptotics

Various test statistics are discussed which can be used for detecting changes in the parameters of an autoregressive time series. In this first part of our study, the limiting behavior of the test statistics is derived under the null hypothesis of no change as well as under alternatives. In a forthcoming second part of our investigation, these asymptotic results will be compared to some corresponding bootstrap procedures, and a small simulation study will be conducted.     

A nonparametric repeated significance test with adaptive target sample size

In this article a general result is derived that, along with a functional central limit theorem for a sequence of statistics, can be employed in developing a nonparametric repeated significance test with adaptive target sample size. This method is used in deriving a repeated significance test with adaptive target sample size for the shift model. The repeated significance test is based on a functional central limit theorem for a sequence of partial sums of truncated observations. Based on numerical results presented in this article one can conclude that this nonparametric sequential test performs quite well.     

Pooling multivariate data under W, LR and LM tests

Two independent random samples are drawn from two multivariate normal populations with mean vectors μ1 and μ2 and a common variance-covariance matrix Σ. Ahmed and Saleh (1990) considered preliminary test maximum likelihood estimator (PMLTE) for estimating μ1 based on the Hotelling's T _N ², when it is suspected that μ1=μ2. In this paper, the PTMLE based on the Wald (W), Likelihood Ratio (LR) and Lagrangian Multiplier (LM) tests are considered. Using the quadratic risk function, the conditions of superiority of the proposed estimator for departure parameter are derived. A max-min rule for the size of the preliminary test of significance is presented. It is demonstrated that the PTMLE based on W test produces the highest minimum guaranteed efficiencies compared to UMLE among the three test procedures.     

尖镰孢菌F.oxysporum L19内切纤维素酶诱导碳源的研究

以在自然界中筛选到的一株产纤维素酶的丝状真菌尖镰孢菌F.oxysporumL19为材料,定时测定尖镰孢菌在10种碳源中的纤维素酶活力,发现酶的合成受培养基中碳源种类的调节控制。结构相对完整的纤维类物质(微晶纤维素、TYPE50、CMC、醋酸纤维素)诱导活性较高,二糖(乳糖、麦芽糖、蔗糖)和单糖(葡萄糖和D-木糖)几乎没有诱导作用,麸皮汁液体培养液表现出了较高的诱导活力。菌丝在麸皮汁培养液上的生长状况的研究表明,菌丝的生长情况与酶的产生存在不同步性。这为下一步酶的纯化和分子生物学的研究中选择不同生长期的培养也提供了依据。     

Robust estimating equation based on statistical depth

In this paper the estimating equation is constructed via statistical depth. The obtained estimating equation and parameter estimation have desirable robustness, which attain very high breakdown values close to 1/2. At the same time, the obtained parameter estimation still has ordinary asymptotic behaviours such as asymptotic normality. In particular, the robust quasi likelihood and depth-weighted LSE respectively for nonlinear and linear regression model are introduced. A suggestion for choosing weight function and a method of constructing depth-weighed quasi likelihood equation are given. This paper is supported by NNSF projects (10371059 and 10171051) of China.     

OUTSOURCING WHEN INVESTMENTS ARE SPECIFIC AND INTERRELATED

Using the universe of large Canadian manufacturing firms in 1988 and 1996, we investigate to what extent outsourcing patterns concord with the predictions of a simple property rights model. The unique availability of disaggregate information on outputs as well as inputs permits the construction of a detailed measure of vertical integration. We rely on five measures of technological intensity to proxy for investments that are likely to be specific to a buyer–seller relationship. A theoretical model that allows for varying degrees of investment specificity and interrelatedness—externalities between buyer and supplier investments—guides the analysis. Property rights predictions on the link between investment intensities and optimal ownership are strongly supported, but only for transactions with low interrelatedness. High specificity and low risk of appropriation strengthen the predictions in the model and in the data.     

EDF tests of goodness of fit for transform-both-sides models

Very often in regression analysis, a particular functional form connecting known covariates and unknown parameters is either suggested by previous work or demanded by theoretical considerations so that the deterministic part of the responses has a known form. However, the underlying error structure is often less well understood. In this case, the transform-both-sides (TBS) models are appropriate. In this paper we generalize the usual TBS models and develop tests to assess goodness of fit when fitting TBS or GTBS models. Parameter estimation is discussed, and tests based on the Cramér-von Mises statistic and the Anderson-Darling statistic are presented with a table suitable for finite-sample applications.     

《西北农林科技大学学报》70年发展史略

对《西北农林科技大学学报》创刊70年来的发展变迁历史进行了整理与回顾,简述了其创刊背景,并以其刊名变更为主线,将其发展过程分为初创与发行、确立与提高、稳定与发展、成熟与扩展4个阶段,对各个阶段的发展历史和特点进行了勾勒和分析,并对今后的发展目标进行了展望。     

克孜尔石窟年代研究和碳十四测定数据的应用

本文介绍了克孜尔石窟年代分期的几种意见,碳十四测定为克孜尔石窟年代分期研究开辟了新的途径。科学技术的发展、科学测定方法的进步和完善,是解决石窟分期问题的希望所在。     

The effect of mixing-distribution misspecification in conjugate mixture models

Parametric mixture models are commonly used in the analysis of clustered data. Parametric families are specified for the conditional distribution of the response variable given a cluster-specific effect, and for the marginal distribution of the cluster-specific effects. This latter distribution is referred to as the mixing distribution. If the form of the mixing distribution is misspecified, then Bayesian and maximum-likelihood estimators of parameters associated with either distribution may be inconsistent. The magnitude of the asymptotic bias is investigated, using an approximation based on infinitesimal contamination of the mixing distribution. The approximation is useful when there is a closed-form expression for the marginal distribution of the response under the assumed mixing distribution, but not under the true mixing distribution. Typically this occurs when the assumed mixing distribution is conjugate, meaning that the conditional distribution of the cluster-specific parameter given the response variable belongs to the same parametric family as the mixing distribution.