Estimating the number of classes

Estimating the unknown number of classes in a population has numerous important applications. In a Poisson mixture model, the problem is reduced to estimating the odds that a class is undetected in a sample. The discontinuity of the odds prevents the existence of locally unbiased and informative estimators and restricts confidence intervals to be one-sided. Confidence intervals for the number of classes are also necessarily one-sided. A sequence of lower bounds to the odds is developed and used to define pseudo maximum likelihood estimators for the number of classes.Comment: Published at http://dx.doi.org/10.1214/009053606000001280 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Pricing Limited Partnerships in the Secondary Market

This study investigates the pattern of prices for multiple partnerships sold in the secondary market. In the model, the partnership buyer prefers to purchase the units sequentially since sellers have varying desires to sell. The benefit of a sequential purchase strategy is partially offset by rational sellers who demand higher prices in earlier sales since the possibility of future sales reduces the sellers’ eagerness to sell in earlier rounds. If this strategic component is sufficiently large, a pattern of decreasing prices should be observed. Using a panel dataset comprised of 52,679 transactions from eighteen real estate limited partnerships, and after controlling for performance characteristics, the study finds that prices decrease over time, thus indicating a significant strategic component in this market.

Remote Sensing Spatiotemporal Assessment of Nitrogen Concentrations in Tampa Bay, Florida due to a Drought

A long-term low nitrogen to phosphorus (N:P) ratio in the Tampa Bay, Florida, estuary system suggests that nitrogen is more limiting than phosphorus. However, south Florida suffered from a drought around 2007, and the reduction in runoff flowing into the bay affected local ecosystem dynamics. This study presents a remote sensing study to retrieve spatiotemporal patterns of total nitrogen (TN) concentrations in Tampa Bay under drought impacts through the integration of Moderate Resolution Imaging Spectroradiometer (MODIS) images and a genetic programming (GP) model. Research findings show that the drought impact on TN in Tampa Bay is both a seasonal and yearly phenomenon. Without the presence of ocean water intrusion, the whole bay would show a relatively uniform TN distribution during the drought period until the flow input from rivers returned to normal. Based on yearly comparisons, temperature could be the limiting factor on the plankton growth in Tampa Bay. To further substantiate the credibility of a nutrient estimation algorithm, a k-means clustering analysis was conducted to demonstrate sea-bay-land interactions among ebbs, tides, and river discharges. The seasonal cluster distribution in 2007 is generally consistent with the conventional segments division of Tampa Bay