Identity, Leibniz's Law and Non-transitive Reasoning

Arguments based on Leibniz's Law seem to show that there is no room for either indefinite or contingent identity. The arguments seem to prove too much, but their conclusion is hard to resist if we want to keep Leibniz's Law. We present a novel approach to this issue, based on an appropriate modification of the notion of logical consequence.     

Fragmentation of metal particles during heterogeneous explosion

Shock Waves - Heterogeneous explosives contain a mixture of standard explosive material and reactive metal particles. The inclusion of metal particles alters the energy density and energy release...     

Simulation methodology — An introduction for queueing theorists

Simulation is a widely used methodology for queueing systems. Its superficial simplicity hides a number of pitfalls which are not all as well known as they should be. In particular simulation experiments need careful design and analysis as well as good presentations of the results. Even the elements of simulation such as the generation of arrival and service times have a chequered history with major problems lying undiscovered for 20 years. On the other hand, good simulation practice can offer much more than is commonly realized.     

Assessing and accounting for time heterogeneity in stochastic actor oriented models

This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijders (Sociological Methodology. Blackwell, Boston, pp 361-395, 2001) which are meant to study the evolution of networks. SAOMs model social networks as directed graphs with nodes representing people, organizations, etc., and dichotomous relations representing underlying relationships of friendship, advice, etc. We illustrate several reasons why heterogeneity should be statistically tested and provide a fast, convenient method for assessment and model correction. SAOMs provide a flexible framework for network dynamics which allow a researcher to test selection, influence, behavioral, and structural properties in network data over time. We show how the forward-selecting, score type test proposed by Schweinberger (Chapter 4: Statistical modeling of network panel data: goodness of fit. PhD thesis, University of Groningen 2007) can be employed to quickly assess heterogeneity at almost no additional computational cost. One step estimates are used to assess the magnitude of the heterogeneity. Simulation studies are conducted to support the validity of this approach. The ASSIST dataset (Campbell et al. Lancet 371(9624):1595-1602, 2008) is reanalyzed with the score type test, one step estimators, and a full estimation for illustration. These tools are implemented in the RSiena package, and a brief walkthrough is provided.     

Uses and abuses of statistical simulation

More and more problems are being tackled by simulation as large computing costs per hour approach those of mathematicians' time. Abuses of simulation arise from ignorance or careless use of little understood procedures, and some of the fundamental tools of the subject are much less well understood than commonly supposed. This is illustrated here by the saga of pseudorandom number generators, normal variate generators and the analysis of queueing system simulations. On the positive side, genuinely new uses of simulation are appearing, particularly in statistical inference. These are exemplified by recursive algorithms for simulating complex systems and simulation-based likelihood inference for point processes.     

Pesticide residues on fruits and vegetables from Ontario, Canada, 1991-1995

For the 5-year period 1991 to 1995, 1536 vegetable and 802 fruit samples were analyzed. The purpose of this study was to determine if pesticides were present on Ontario-produced fruits and vegetables, and if so, to determine if residues violated maximum residue limits (MRLs). Overall, 31.5% of the samples had no detectable pesticide residues, whereas 68.5% contained one or more residues. Most of the residues were present at very low concentrations; 48% of the detections were < 0.1 parts per million (ppm), and 86% were < 1 ppm. However, violations of MRL were observed in only 3.2% of the vegetables samples and 3.1% of the fruit samples. In addition, 4.8% of the samples contained a "technical" violation, that is, there was no specified MRL for the pesticide-commodity combination and the residues exceeded 0.1 ppm. Of the detectable residues, 63% were < 10% of the MRL, whereas 89% were < 50% of the MRL. More fruit samples (91.4%) had a detectable residue, compared with vegetable samples (56.6%). Fruit is often treated close to harvest or post harvest to ensure that wholesome produce reaches the consumer. Forty-six percent of the samples contained 2 or more residues, and 2% of all samples had more than 5 different pesticides detected; fruit samples tended to have more multiple residues. The most frequently found pesticides were captan, the dithiocarbamate fungicides, endosulfan, azinphos-methyl, phosmet, parathion, and iprodione. These pesticides were also used in the greatest quantity for crop production. Overall, the data agree fairly closely with those reported for the U.S. Department of Agriculture Pesticide Data Program because the 2 programs have similar analytical goals and objectives.