Team-oriented process programming

Team-oriented process programming promises to provide significant support for the planning, directing, and controlling of software engineering projects. In this paper we apply process programming to software engineering teams and show how this can provide powerful new capabilities for the management of software projects. We identify key issues which must be addressed to apply process programming to teams, and present our vision for team-oriented process programming

Serial Persistence in Equity REIT Returns

Annual and monthly REIT returns display statistically significant serial persistence, although the two types of persistence behavior are qualitatively different. By contrast, quarterly REIT returns do not display serial persistence. This strongly suggests that linear multifactor market models cannot describe REIT investment behavior. Annual REIT returns fail to reflect corresponding persistence behavior in underlying real estate returns precisely when the REITs are large enough to attract institutional investor interest. Institutional investors move in and out of large-capitalization REITs in ways that negatively impact investment returns.

The Magnitude of Random Appraisal Error in Commercial Real Estate Valuation

Analysis of more than seven hundred pairs of simultaneous independent appraisals of institutional-grade commercial properties shows that the standard deviation of the random component of appraisal error is approximately 2%. Random appraisal error appears constant across both time and the institutional-grade investment universe, except during infrequent periods of real estate market gridlock. Most appraisal error is deterministic in nature, even though it usually appears random in routine cross-sectional analysis. Such appraisal error can be constrained and reduced by investment management control systems.

Systematic Behavior in Real Estate Investment Risk: Performance Persistence in NCREIF Returns

Serial dependence of total annual returns in the NCREIF database is shown to be statistically significant in the first and fourth quartiles of disaggregated data between 1978 and 1994. More precisely, superior performance is generally followed by continued superior performance, and inferior performance is generally followed by continued inferior performance. In contrast, there is virtually no evidence to support serial dependence in the second or third quartiles, whether combined or taken separately. The empirical rejection of serial independence among real estate returns calls into question the conclusions of research based upon models that incorporate the assumption of serial independence.

The Shape of Australian Real Estate Return Distributions and Comparisons to the United States

Investment risk models with variance provide a better description of distribution of individual property returns in the Property Council of Australia data base from 1985 to 1996 than normally distributed risk models. The shape of the distribution of Australian property returns is virtually indistinguishable from the shape of United States property returns in the NCREIF Property Index for the years 1980 to 1992. Australian real estate investment risk is heteroscedastic, like its US counterpart, but the characteristic exponent of the investment risk function is constant across time and property type. It follows that portfolio management and asset diversification techniques that rely upon finite-variance statistics are as ineffectual for the Australian real estate market as they have been found to be for the United States.

The Dimensions of Driver Performance during Secondary Manual Tasks

This analysis identified the underlying dimensions of driver performance using data obtained from drivers engaged in secondary manual tasks. Randomly chosen subjects balanced for age and gender used one of five advanced navigation and communication systems while driving on a closed roadway. Fifteen driver performance variables were averaged and standardized across subjects for 79 tasks. There were high correlations between all variables. Principal Component Analysis (PCA) found that the vector of loadings defining the first principal component (PC1) was positive for all 15 variables, accounting for 61 percent of the total variation across all tasks. It is interpreted as overall driver demand. PC2 loaded with one sign on event detection and response variables, but opposing sign on visual-manual workload variables. It identified tasks making drivers more inattentive to outside events than expected, given a task’s visual-manual workload, and accounted for 17 percent of total variation. It is interpreted as low-workloadbut-high-inattentiveness. PC3 had loadings of opposing sign for peripheral vs. central event variables (5 percent of total variation). It is interpreted as peripheral insensitivity. The first three components together accounted for 83 percent of total variation, which is deemed substantial. Thus most of the information available through the 15 original variables can be summarized by only three PC variables. Because the vectors of loadings defining the components are orthogonal to each other as defined by PCA, no single variable by itself can capture all the important variations in driver performance during secondary manual tasks. A multivariate design and analysis is required

Habitat Relationships of Landbirds in the Northern Region, USDA Forest Service

A series of first-generation habitat-relationships models for 83 bird species were detected in a 3-year study on point counts conducted in association with the USDA Forest Service\u27s Northern Region Landbird Monitoring Program. The models depict probabilities of detection for each of the bird species on 100-m-radius, 10-minute point counts conducted across a series of major vegetation cover types. Based on these models, some bird species appear to be restricted in their habitat distribution to: (1) postfire, standing-dead forests, (2) relatively uncut, older forests, (3) harvested forest types, (4) marshes, (5) riparian environments, and (6) grasslands and sagebrush. Such restricted distributions highlight the need to provide adequate amounts of these cover types to maintain viable species populations. Many bird species were relatively abundant in harvested forests, suggesting a need for nesting success studies because timber harvesting creates unnatural cover types that may elicit settling responses by species that are programmed to respond to similar naturally occurring cover types. Thus, these unnatural cover types could be acting as ecological traps, where species are being attracted to sites where suitability is relatively poor. These preliminary results demonstrate the utility of a landbird monitoring program, and suggest that agencies such as the Forest Service should consider broadening the indicator species concept to monitor groups of species (such as landbirds and butterflies) that can be easily sampled with a single field method. The list of species covered by this program is indeed large enough and ecologically broad enough to help managers predict and monitor the effects of management activities on almost all the major vegetation types in the region. The detail and region-specific nature of this information can be matched by no other database in existence on landbirds, and the information should prove useful to land managers in planning areas that might consist of alternative cover types