Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent

As one of the most sensitive areas responding to global environmental change, especially global climate change, Qinghai-Tibet Plateau has been recognized as a hotspot for coupled studies on global terrestrial ecosystem change and global climate change. As an important component of terrestrial ecosystems, vegetation dynamic has become one of the key issues in global environmental change, and numerous case studies have been conducted on vegetation dynamic trend in different study periods. However, few are focused on the quantitative analysis of the consistency of vegetation dynamic trends after the study periods. In the study, taking Qinghai-Tibet Plateau as a case, vegetation dynamic trend during 1982-2003 were analyzed, with the application of the method of linear regression analysis. The results showed that, vegetation dynamics in Qinghai-Tibet Plateau experienced a significant increasing as a whole, with nearly 50% forest degradation in the study period. And among the 7 kinds of vegetation types, the change of forest was the most fluctuant with desert the least one. Furthermore, the consistency of vegetation dynamic trends after the study period, was quantified using Hurst Exponent and the method of R/S analysis. The results showed high consistency of future vegetation dynamic trends for the whole plateau, and inconsistent areas were mainly meadow and steppe distributed in the middle or east of the plateau. It was also convinced that, vegetation dynamic trends in the study area were significantly influenced by topography, especially the elevation.     

Consistency of dogs’ reactions to threatening cues of an unfamiliar person

Reliability is one of the most important aspects of the behaviour observations measuring personality traits in animals. The most fundamental way to test reliability is the assessment of the test–retest consistency. On the other hand, in situations where social interaction between a human participant and the animal subject is at the scope of the study, the behaviour of the humans in the test situation should be restricted by a set of rules. However, if more than one experimenter participates in the observations, the similarity of the behaviour of different persons is an important aspect of the reliability of the study.In our first study we investigated the consistency of dogs’ behaviour during approach by a person in a friendly and in a threatening way, repeating the test either immediately after the first test or at least 6 months later. We found that the dogs’ sensitivity to the human's behavioural cues in this situation proved to be consistent over repetition when the second test was performed approximately 1 year after the first test, but it was not the case when the time elapsed between test occasions was a few seconds. The detailed analysis indicated that dogs performing extreme behaviour (friendly or threatening) tended to show more conservative responses than dogs showing intermediate reactions when the stranger approached threateningly. Nonetheless, the reaction of the dogs failed to be in accordance with the opinion of the owners about the dogs’ behaviour in similar situations in everyday life.In the second study we examined the consistency of the dogs’ behaviour in the same situation when confronted with two different unfamiliar persons immediately after each other. The consistency of the dogs’ response to the two experimenters was found to be reliably high.In sum, this test procedure proved to be reliable enough to be a valuable measure of a definite part of the personality characters of dogs.     

Extended Bayesian information criteria for model selection with large model spaces

The ordinary Bayesian information criterion is too liberal formodel selection when the model space is large. In this paper,we re-examine the Bayesian paradigm for model selection andpropose an extended family of Bayesian information criteria,which take into account both the number of unknown parametersand the complexity of the model space. Their consistency isestablished, in particular allowing the number of covariatesto increase to infinity with the sample size. Their performancein various situations is evaluated by simulation studies. Itis demonstrated that the extended Bayesian information criteriaincur a small loss in the positive selection rate but tightlycontrol the false discovery rate, a desirable property in manyapplications. The extended Bayesian information criteria areextremely useful for variable selection in problems with a moderatesample size but with a huge number of covariates, especiallyin genome-wide association studies, which are now an activearea in genetics research.     

On the accuracy of efficiency of estimating equation approach

Liang and Zeger (1986, Biometrika 73, 13-22) introduced a generalized estimating equation (GEE) approach based on a working correlation matrix to obtain efficient estimators of regression parameters in the class of generalized linear models for repeated measures data. As demonstrated by Crowder (1995, Biometrika 82, 407-410), because of uncertainty of the definition of the working correlation matrix, the Liang-Zeger approach may, in some cases, lead to a complete breakdown of the estimation of the regression parameters. After taking this comment of Crowder into account, recently Sutradhar and Das (1999, Biometrika 86, 459-465) examined the loss of efficiency of the regression estimators due to misspecification of the correlation structures. But their study was confined to the regression estimation with cluster-level covariates, as in the original paper of Liang and Zeger. In this paper, we study this efficiency loss problem for the generalized regression models with within-cluster covariates by utilizing the approach of Sutradhar and Das (1999).     

A Jackknife Variance Estimator for Unistage Stratified Samples with Unequal Probabilities

Existing jackknife variance estimators used with sample surveyscan seriously overestimate the true variance under unistagestratified sampling without replacement with unequal probabilities.A novel jackknife variance estimator is proposed which is asnumerically simple as existing jackknife variance estimators.Under certain regularity conditions, the proposed variance estimatoris consistent under stratified sampling without replacementwith unequal probabilities. The high entropy regularity conditionnecessary for consistency is shown to hold for the Rao–Sampforddesign. An empirical study of three unequal probability samplingdesigns supports our findings.     

An exact test for detecting inconsistency in readers interpretation over time in screening mammograms

Radiologists' interpretation on screening mammograms is measured by accuracy indices such as sensitivity and specificity. The hypothesis that radiologists' interpretation on screening mammograms is constant across time can be tested by measuring overdispersion. However, small sample sizes are problematic for the accuracy of asymptotic approaches. In this article, we propose an exact conditional distribution for testing overdispersion of the binomial assumption that is assumed for the accuracy indices. An exact p -value can be defined from the developed distribution. We also describe an algorithm for computing this exact test. This proposed method is applied to data from a study in reading screening mammograms in a population of US radiologists (Beam et al., 2003). The exact method is compared analytically with a currently available method based on large sample approximations.     

Consistency of interneuronal group formation in response to stimulation of identified cells

In crayfish stimulation of abdominal positioning interneurons (APIs) recruits other interneurons producing various abdominal movements. We investigated whether: (1) the same API from different preparations activated a similar number or group of interneurons, (2) different APIs activated different groups, and (3) repeated stimulation of an API consistently affected a similar set of interneurons. To quantify the similarities and differences of the recruited interneuronal groups we compared the number of interneurons affected, their firing frequencies, and motor outputs. Three types of APIs (Curly Q, L and T) were identified and each type was stimulated in three preparations. Our results showed that for the Curly Q and L cells, each cell type activated interneuronal groups that were statistically similar in number and firing frequency. The T cell activated interneuronal groups that were more variable. Some APIs generally provided a repeatable motor output; all did not. The interneuronal groups activated by the Curly Q, L and T cells were very different from each other. Repeated stimulation of one Curly Q cell affected similar although not identical sets of interneurons. These data suggest that repeated motor outputs could be produced by a similar but not identical group of cells. Accepted: 29 September 1997     

A note on the occasional instability of detrending in correspondence analysis

When the two first eigenvalues of correspondence analysis are close to each other, their order can be reversed due to random variation in the data. The first axis can actually be in any direction in the plane defined by the two axes. However, the configuration of the points in the plane can remain unchanged but their projections onto any line in the plane can be very variable. The ordering in the first axis is preserved in detrending. The second axis is detrended with respect to the first one and therefore very variable configurations result when the orientation of the first axis in the plane is changed. This can lead to a situation where the detrended solutions are very unstable under random variation and therefore they can be only casually interpretable.