Estimating the total number of distinct species when quadrat sampling or sampling of elements is used

The problem of estimating the total number T of distinct species in some specified region based on a random sample from the region is discussed. Two sampling procedures are of interest, sampling by elements and quadrat sampling;In the case of sampling by elements, we assume that the investigator has available a list containing a total of M known species that he believes could be found in that particular region, M 0 and known, to the relative abundances of the species in group two. Admissible estimators are also presented for the case where [beta] → 0 and [beta] → [infinity];In the case of quadrat sampling, two models are discussed. The first is basically a version of the Efron and Thisted (1976) model adapted to the case of quadrat sampling. Some Empirical Bayes estimators for T are derived. It is seen that these estimators are easy to apply in practical situations, they give very good point estimates, they take into account how much the sample represents the whole region and they give more reasonable estimates than the jackknife and the bootstrap estimators proposed by Heltshe and Forrester (1983), and Smith and Belle (1984). Some discussion about the effect of quadrat area and sampled area is given. The second model discusses the case where the species in the region have exactly two replicas. Admissible stepwise Bayes estimators are derived for T in this case and an application in archaeology is presented;References. (1) Efron, B. and Thisted, R. 1976. Estimating the number of unseen species: How many words did Shakespeare know? Biometrika 63:435-447. (2) Heltshe, J. F. and Forrester, N. E. 1983. Estimating species richness using the jackknife procedure. Biometrics 39:1-11. (3) Smith, E. P. and Belle, G. V. 1984. Nonparametric estimation of species richness. Biometrics 40:119-129

Using Geostatistics to Estimate the Variability of Autocorrelated Processes

Statistical quality control is used to detect changes in the parameters values of the process which usually are estimated under the assumption of independence of the sampling units with respect to the quality characteristic. However, this is questionable for many processes. The main objective of this paper is to present estimators for the variance of autocorrelated processes by using Geostatistics methodology. With this new procedure the usual Shewhart’s control charts still can be used to monitor the quality of the process. A Monte Carlo simulation study showed that the proposed estimators have good performance

A novel experience in the use of control charts for the detection of nosocomial infection outbreaks

OBJECTIVE: This study aims to compare different control charts to monitor the nosocomial infection rate per 1,000 patient-days. METHODS: The control charts considered in this study were the traditional Shewhart chart and a variation of this, the Cumulative Sum and Exponentially Weighted Moving Average charts. RESULTS: We evaluated 238 nosocomial infections that were registered in the intensive care unit and were detected by the Committee for Nosocomial Infection Control in a university hospital in Belo Horizonte, Brazil, in 2004 and 2005. The results showed that the traditional Shewhart chart was the most appropriate method for monitoring periods with large deviations, while the Exponentially Weighted Moving Average and Cumulative Sum charts were better for monitoring periods with smaller deviations of the mean infection rate. CONCLUSION: The ability to detect nosocomial outbreaks was improved by using the information provided by all three different control charts

On Capability Indices for Multivariate Autocorrelated Processes

In this paper the effects of the autocorrelation on some multivariate capability indices commonly used for independent processes are discussed and a correction is proposed. Some results are shown for VARMA(1,1) and VAR(1) time series processes under the multivariate normality assumption and the proportion of non-conforming units is calculated for some bivariate VAR(1) models. An extension of Veevers capability index for non-centered processes is also a subject addressed in this paper. An example of application in blast charcoal furnace pig iron process is presented and bootstrap is used to build confidence intervals for its true capability value as well as to evaluate the performance of the capability estimators. Similar as to what is already known for univariate processes the results showed that autocorrelation has a large impact in the multivariate capabilities indices. This paper also shows that some care should be taken when using Niverthi and Dey’s capabilities indices since they are very sensitive to any deviations from the process means to the specification means up to a point that a capable process might be considered non-capable

In vitro dissolution kinetic for mycophenolic acid derivatives tablets

Micofenolato de mofetila (MMF) e micofenolato sódico (MPS) são, respectivamente, éster e sal sódico do ácido micofenólico. Os fármacos possuem características farmacocinéticas distintas em função das diferenças na estrutura molecular, nas propriedades físico-químicas e nas formulações administradas. Neste trabalho, os perfis de dissolução dos medicamentos referências foram testados em diferentes meios de dissolução com o objetivo de avaliar o efeito da variação de pH, a cinética de dissolução e o modelo estatístico mais adequado para prever a dissolução dos fármacos. A liberação dos fármacos foi determinada com método validado por espectroscopia no ultravioleta, λ 250 nm. O método mostrou-se seletivo, linear, preciso e exato para dissolução de MMF em 0,1 M HCl e MPS em tampão fosfato pH 6,8. Os modelos cinéticos de dissolução de ordem zero, primeira ordem, Higuchi, Hixson-Crowell e Weibull foram aplicados com o objetivo de selecionar aquele com o melhor ajuste por regressão linear. Os parâmetros de regressão foram estimados e os ajustes dos modelos foram verificados pelos resíduos e coeficientes de determinação. Os resíduos obtidos foram aleatórios, independentes, apresentaram variância constante e seguiram a distribuição normal. Os valores de R² (74,7% para MMF e 95,8% para MPS) indicaram bom ajuste da regressão de Weibull para explicar a variabilidade e estimar a liberação dos fármacos.Mycophenolate mofetil (MMF) and mycophenolate sodium (MPS) are an ester and a salt of mycophenolic acid. They have different kinetic in vivo characteristics due to differences in molecular structures, physicochemical properties and formulations administered. In this study, dissolution profiles of reference products were tested in different media to evaluate the effect of pH, kinetic dissolution and the best statistical model that can be used to predict the release of both drugs. The drug release was determined by using a validated ultraviolet spectrophotometry method, λ 250 nm. The method showed to be selective, linear, precise and accurate for MMF in 0.1 M HCl and MPS in sodium phosphate buffer pH 6.8. Dissolution kinetics models of zero order, first order, Higuchi, Hixson-Crowell and Weibull were applied to data in order to select the best fit by linear regression. The regression parameters were estimated and the models were evaluated with the results of residuals and coefficient of determination. The residuals obtained from dissolution kinetics models were random, uncorrelated, and normally distributed with constant variance. The R² values (74.7% for MMF and 95.8% for MPS) demonstrated good ability of the Weibull regression to explain the variability and to predict the drugs' release