This paper presents the design of Sharpened three stage CIC filter for decimation. The proposed decimation filter has Cascaded-Integrator Comb filter as first stage, Sharpened Cascaded-Integrator Comb filter as second and third stage. The CIC filter at first stage operates at input sampling rate, sharpened second stage operates at lower rate as compared to first stage and sharpened third stage ...

Pharmacokinetic studies are commonly performed using the two-stage approach. The first stage involves estimation of pharmacokinetic parameters such as the area under the concentration versus time curve (AUC) for each analysis subject separately, and the second stage uses the individual parameter estimates for statistical inference. This two-stage approach is not applicable in sparse sampling si...

Insect populations vary in the proportion of individuals exhibiting a particular ‘state’ (e.g., developmental stage, sex, egg load, or nutritional status). Because an insect’s developmental state often determines both its size and its behavior, it is likely that this will also affect the probability of being sampled. We propose that a comprehensive approach to pest management must consider the ...

We consider two-stage case-control designs for testing associations between single nucleotide polymorphisms (SNPs) and disease, in which a subsample of subjects is used to select a panel of "tagging" SNPs that will be considered in the main study. We propose a pseudolikelihood [Pepe and Flemming, 1991: JASA 86:108-113] that combines the information from both the main study and the substudy to t...

A nonparametric model-assisted survey estimator for status estimation based on local polynomial regression is extended to incorporate spatial auxiliary information. Under mild assumptions, this estimator is design-unbiased and consistent. Simulation studies show that the nonparametric regression estimator is competitive with standard parametric techniques when a parametric specification is corr...

Reliable estimates of population size are important for developing and monitoring health programs in at-risk populations. Laska, Meisner, and Siegel (Biometrics 1988;44:461-72) developed an unbiased estimator for the size of a population at a single venue based on a single sample. Because many populations of interest are not contained within a single venue, this article generalizes the Laska, M...

Preexisting computerized databases are potentially valuable sources of epidemiologic data. Since such databases are infrequently created specifically for etiologic research, data may be available for the exposure of interest and, through record linkage, for the endpoint of interest, but lacking for potential confounders. Because of the size of these databases, two-stage sampling is an efficient...

We propose a tractable approximation scheme for convex (not necessarily linear) multi-stage robust optimization problems. We approximate the adaptive decisions by finite linear combinations of prescribed basis functions and demonstrate how one can optimize over these decision rules at low computational cost through constraint randomization. We obtain a-priori probabilistic guarantees on the fea...

We consider local polynomial regression estimation for nite population totals in two-stage element sampling. The estimators are linear combinations of es-timators of cluster totals with weights that are calibrated to known control totals. The estimators are asymptotically design-unbiased and consistent under mild assumptions. We provide a consistent es-timator for the design mean squared error ...

To evaluate the performance of the empirical predictors presented in San Martino et al. (2005), we compute the cases where they are the best, “equivalent” to the best (tables 1) or poor (table2). We consider only the case of equal unknown within cluster variances. First, we consider the cases in which each of the proposed predictors has the best performance, i.e. we compute the percentage of ca...