Spatial methods for plot-based sampling of wildlife populations

Classical sampling methods can be used to estimate the mean of a finite or infinite population. Block kriging also estimates the mean, but of an infinite population in a continuous spatial domain. In this paper, I consider a finite population version of block kriging (FPBK) for plot-based sampling. The data are assumed to come from a spatial stochastic process. Minimizing mean-squared-prediction errors yields best linear unbiased predictions that are a finite population version of block kriging. FPBK has versions comparable to simple random sampling and stratified sampling, and includes the general linear model. This method has been tested for several years for moose surveys in Alaska, and an example is given where results are compared to stratified random sampling. In general, assuming a spatial model gives three main advantages over classical sampling: (1) FPBK is usually more precise than simple or stratified random sampling, (2) FPBK allows small area estimation, and (3) FPBK allows nonrandom sampling designs.

Reverse Engineering the Structural and Acoustic Behavior of a Stradivari Violin

There is a tremendous amount of mystery that surrounds the instruments of Antonio Stradivari. There have been many studies done in the past, but no one completely understands exactly how he made his instruments, or why they are still considered the best in the world. This project is designed to develop an engineering model of one of Stradivari's violins that will accurately simulate the structural and acoustic behavior of the instrument. It also hopes to shine some light on what makes the instruments of Stradivari unique when compared to other violins. It will focus on geometry and material properties, utilizing several modern engineering tools, including CT scanning, experimental modal analysis, finite element analysis, correlation techniques, and acoustic synthesis.

COEFPLOT: Stata module to plot regression coefficients and other results

coefplot plots results from estimation commands or Stata matrices. Results from multiple models or matrices can be combined in a single graph. The default behavior of coefplot is to draw markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce various other types of graphs.

ADDPLOT: Stata module to add twoway plot objects to an existing twoway graph

addplot adds twoway plot objects to an existing twoway graph. This is useful if you want to add additional objects such as titles or extra data points to a twoway graph after it has been created. Most of what addplot can do, can also be done by rerunning the original graph command including additional options or plot statements. addplot, however, might be useful if you have to modify a graph for which you cannot rerun the original command, for example, because you only have the graph file but not the data that were used to create the graph. Furthermore, addplot can do certain things that would be difficult to achieve in a single graph command (e.g. customizing individual subgraphs within a by-graph). addplot also provides a substitute for some of the functionality of the graph editor.

Unsane taukef : liturgick song of the Hebrew New Year and Day of Atonement ; [violin solo]

by Joachim Kurantmann

The menorah : from Theodore Herzl ; for solo, tenor or soprano, violin and piano ; with 4 texts: Hebrew, Jewish, English and German

composed by A. Haitmann

The Ghetto song : Rachel oh Rachel ; for solo, tenor or soprano, violin and piano ; with 4 texts: Hebrew, Jewish, English and German

composed by A. Haitmann. [Words] from Hugo Zuckermann

David's violin : opera

by Lateiner & Mogulesco. Arr. by H. A. Russotto

Odesser bulgar : violin

by Abe Schwartz. Arr. by H. A. Russotto