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## A model for a comprehensive LIMS

### Advanced LIMS Technology (1995-01-01): 15-36 , January 01, 1995

Demands on many laboratory organizations are becoming a driving force to automate analytical procedures. Automation, which is generally focused at the bench, allows an analyst to complete more work per unit time, resulting in higher productivity. Laboratory Information Management Systems (LIMS) have been developed to carry out many associated administrative tasks and procedures required to run a laboratory. However, many organizations often take a narrow view of both a laboratory and the functions that can be automated, preventing them from extending automation to provide real scientific and business benefits.

## The Star*s Family: An example of comprehensive yellow-page services

### Information & On-Line Data in Astronomy (1995-01-01) 203: 195-205 , January 01, 1995

In the book *Databases & On-line Data in Astronomy* (Albrecht & Egret 1991), the chapter entitled *Astronomical Directories* (Heck, 1991) was essentially dealing with classical publications on paper: directories of organizations, lists of electronic addresses, and so on. Some files started to be retrievable electronically. In Sect. 8 (*Future Trends*) of that chapter, we were looking forward to using on-line and networking facilities that have become a daily reality since.

## The Database for Galactic Open Clusters (BDA)

### Information & On-Line Data in Astronomy (1995-01-01) 203: 127-138 , January 01, 1995

The database for stars in galactic open clusters (BDA) has been developed since 1987 at the Institute for Astronomy (University of Lausanne). The extensive collection of observational data covers most significant domains and concerns about 100,000 stars in some 500 NGC, IC and anonymous clusters.

## Mixed Models

### Exact Statistical Methods for Data Analysis (1995-01-01): 242-271 , January 01, 1995

In Chapter 8, we were interested in the effects of certain treatments, certain brands of a product, certain diet plans, and so on. The levels (e.g. competing treatments) of each factor were considered as deliberate choices of an experimenter and the models we encountered in that chapter allowed the experimenter to compare the effects of competing treatments. The models that we studied in the previous chapter are called *fixed effects models*. In some other applications, the levels of each factor used in an experimental design are not of particular interest and they are selected at random from a large population of potential levels. Models that incorporate this feature are called *random effects models.* In yet other applications, the levels of some factors are of special interest and deliberately chosen and the levels of other factors are randomly selected. As the underlying models in this situation have some features in common with each of aforementioned model types, such models are referred to as *mixed models.* In many industrial experiments it is important to identify and control major sources of variation, and in such situations random effects models and mixed models arise naturally.

## Matrix-trace Cauchy-Schwarz inequalities and applications in canonical correlation analysis

### Statistical Papers (1995-12-01) 36: 287-298 , December 01, 1995

Various matrix-trace Cauchy-Schwarz and related inequalities involving positive semidefinite matrices are obtained. Applications of some of these results to canonical correlation analysis are presented.

## The empirical linear predictor and its MSE

### Metrika (1995-12-01) 42: 260 , December 01, 1995

## Some Strategic Issues

### Observational Studies (1995-01-01): 225-227 , January 01, 1995

By and large, the discipline of statistics is concerned with the development of correct and effective research designs and analytical methods, together with supporting theory. Here, correct and effective refer to formal properties of the designs and methods. The first nine chapters discussed issues of this sort. In contrast, a strategic issue concerns the impact that an empirical investigation has on its intended audience. Often, the audience is not focused on statistical technique and theory, may have limited training in statistics, and may be comprised of laymen, that is, laymen with respect to their knowledge of statistics. When this is so, strategic issues may arise in which formal properties are weighed against impact on the intended audience.

## Multigaussian models: The danger of parsimony

### Journal of the Italian Statistical Society (1995-06-01) 4: 167-181 , June 01, 1995

### Summary

MultiGaussian models have the intrinsic property of imposing very little continuity to extreme values. If the variable that is being modeled is hydraulic conductivity and the processes being studied are groundwater flow and mass transport, the absence of continuous paths of extreme values will have a retardation effect in the computed travel times. In the case of radionuclide release of nuclear waste from a deep geological repository, underestimation of travel times may lead to unsafe decision making. To demonstrate the impact of the low continuity of extreme value implicit to multiGaussian modes, travel times are computed in a site similar to Finnsjön-one of the sites in crystaline rock studied in Sweden-using two stochastic models with the same histogram and covariance, one of them is multiGaussian, and the other is not and displays high connectivity of extreme high values. The results show that the multiGaussian model leads to less conservative results than the non-multiGaussian one. Invoking the parisimony principle to select a multiGaussian model as the simplest model that can be fully described by a mean value and a covariance function should not be justification enough for such selection. If there is not enough data to characterize the connectivity of the extreme values and therefore distriminate whether a multiGaussian model is appropriate or not, less parismonious models must also be considered.

## Net Premiums

### Life Insurance Mathematics (1995-01-01): 49-57 , January 01, 1995

An insurance policy specifies on the one hand the benefits payable by the insurer (benefits may consist of one payment or a series of payments, see Chapters 3 and 4), and on the other hand the premium(s) payable by the insured. Three forms of premium payment can be distinguished: 1.

One single premium,

2.Periodic premiums of a constant amount (*level* premiums),

Periodic premiums of varying amounts.

## Estimation of a quantile in some nonstandard cases

### Annals of the Institute of Statistical Mathematics (1995-01-01) 47: 105-117 , January 01, 1995

A necessary condition for the asymptotic normality of the sample quantile estimator is*f*(*Q*(*p*))=*F′*(*Q*(*p*))>0, where*Q*(*p*) is the*p*-th quantile of the distribution function*F*(*x*). In this paper, we estimate a quantile by a kernel quantile estimator when this condition is violated. We have shown that the kernel quantile estimator is asymptotically normal in some nonstandard cases. The optimal convergence rate of the mean squared error for the kernel estimator is obtained with respect to the asymptotically optimal bandwidth. A law of the iterated logarithm is also established.