The relationship between absolute and proportion scores of serial order memory: simulation predictions and empirical data

The capability of a feature model of immediate memory (Nairne, 1990; Neath, 2000) to predict and account for a relationship between absolute and proportion scoring of immediate serial recall when memory load is varied (the list-length effect, LLE) is examined. The model correctly predicts the novel finding of an LLE in immediate serial order memory similar to that observed with free recall and previously assumed to be attributable to the long-term memory component of that procedure (Glanzer, 1972). The usefulness of formal models as predictive tools and the continuity between short-term serial order and longer term item memory are considered.

Should optional properties be used in conceptual modelling? A theory and three empirical tests

An important feature of some conceptual modelling grammars is the features they provide to allow database designers to show real-world things may or may not possess a particular attribute or relationship. In the entity-relationship model, for example, the fact that a thing may not possess an attribute can be represented by using a special symbol to indicate that the attribute is optional. Similarly, the fact that a thing may or may not be involved in a relationship can be represented by showing the minimum cardinality of the relationship as zero. Whether these practices should be followed, however, is a contentious issue. An alternative approach is to eliminate optional attributes and relationships from conceptual schema diagrams by using subtypes that have only mandatory attributes and relationships. In this paper, we first present a theory that led us to predict that optional attributes and relationships should be used in conceptual schema diagrams only when users of the diagrams require a surface-level understanding of the domain being represented by the diagrams. When users require a deep-level understanding, however, optional attributes and relationships should not be used because they undermine users' abilities to grasp important domain semantics. We describe three experiments which we then undertook to test our predictions. The results of the experiments support our predictions.

Testing insect movement theory: empirical analysis of pest data routinely collected from agricultural crops

Observations of an insect's movement lead to theory on the insect's flight behaviour and the role of movement in the species' population dynamics. This theory leads to predictions of the way the population changes in time under different conditions. If a hypothesis on movement predicts a specific change in the population, then the hypothesis can be tested against observations of population change. Routine pest monitoring of agricultural crops provides a convenient source of data for studying movement into a region and among fields within a region. Examples of the use of statistical and computational methods for testing hypotheses with such data are presented. The types of questions that can be addressed with these methods and the limitations of pest monitoring data when used for this purpose are discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Choice of Contracts in the British National Health Service: An Empirical Study

Following major reforms of the British National Health Service (NHS) in 1990, the roles of purchasing and providing health services were separated, with the relationship between purchasers and providers governed by contracts. Using a mixed multinomial logit analysis, we show how this policy shift led to a selection of contracts that is consistent with the predictions of a simple model, based on contract theory, in which the characteristics of the health services being purchased and of the contracting parties influence the choice of contract form. The paper thus provides evidence in support of the practical relevance of theory in understanding health care market reform.

An Empirical Examination of the R&D Boundaries of the Firm - A Problem-Solving Perspective

We consider, both theoretically and empirically, how different organization modes are aligned to govern the efficient solving of technological problems. The data set is a sample from the Chinese consumer electronics industry. Following mainly the problem solving perspective (PSP) within the knowledge based view (KBV), we develop and test several PSP and KBV hypotheses, in conjunction with competing transaction cost economics (TCE) alternatives, in an examination of the determinants of the R&D organization mode. The results show that a firm’s existing knowledge base is the single most important explanatory variable. Problem complexity and decomposability are also found to be important, consistent with the theoretical predictions of the PSP, but it is suggested that these two dimensions need to be treated as separate variables. TCE hypotheses also receive some support, but the estimation results seem more supportive of the PSP and the KBV than the TCE.

Frequency-dependent sexual selection with respect to offspring fitness returns is consistent with predictions from rock-paper-scissors dynamics in the European common lizard

Genetic polymorphism can be maintained over time by negative frequency-dependent (FD) selection induced by Rock-paper-scissors (RPS) social systems. RPS games produce cyclic dynamics, and have been suggested to exist in lizards, insects, isopods, plants, and bacteria. Sexual selection is predicted to accentuate the survival of the future progeny during negative FD survival selection. More specifically, females are predicted to select mates that produce progeny genotypes that exhibit highest survival during survival selection imposed by adult males. However, no empirical evidence demonstrates the existence of FD sexual selection with respect to fitness payoffs of genetic polymorphisms. Here we tested this prediction using the common lizard Zootoca vivipara, a species with three male color morphs (orange, white, yellow) that exhibit morph frequency cycles. In a first step we tested the congruence of the morph frequency change with the predicted change in three independent populations, differing in male color morph frequency and state of the FD morph cycle. Thereafter we ran standardized sexual selection assays in which we excluded alternative mechanisms that potentially induce negative FD selection, and we quantified inter-sexual behavior. The patterns of sexual selection and the observed behavior were in line with context-dependent female mate choice and male behavior played a minor role. Moreover, the strength of the sexual selection was within the magnitude of selection required to produce the observed 3-4-year and 6-8 year morph frequency cycles at low and high altitudes, respectively. In summary, the study provides the first experimental evidence that underpins the crucial assumption of the RPS games suggested to exist in lizards, insects, isopods, and plants; namely, that sexual selection produces negative-FD selection. This indicates that sexual selection, in our study exert by females, might be a crucial driver of the maintenance of genetic polymorphisms.

MEPDG Work Plan Task No. 7: Existing Pavement Input Information for the Mechanistic-Empirical Pavement Design Guide, 2009

The objective of this study is to systematically evaluate the Iowa Department of Transportation’s (DOT’s) existing Pavement Management Information System (PMIS) with respect to the input information required for Mechanistic-Empirical Pavement Design Guide (MEPDG) rehabilitation analysis and design. To accomplish this objective, all of available PMIS data for interstate and primary roads in Iowa were retrieved from the Iowa DOT PMIS. The retrieved data were evaluated with respect to the input requirements and outputs for the latest version of the MEPDG software (version 1.0). The input parameters that are required for MEPDG HMA rehabilitation design, but currently unavailable in the Iowa DOT PMIS were identified. The differences in the specific measurement metrics used and their units for some of the pavement performance measures between the Iowa DOT PMIS and MEPDG were identified and discussed. Based on the results of this study, it is recommended that the Iowa DOT PMIS should be updated, if possible, to include the identified parameters that are currently unavailable, but are required for MEPDG rehabilitation design. Similarly, the measurement units of distress survey results in the Iowa DOT PMIS should be revised to correspond to those of MEPDG performance predictions. *******************Large File**************************

MEPDG Work Plan Task No. 8: Validation of Pavement Performance Curves for the Mechanistic-Empirical Pavement Design Guide, 2009

The objective of this research is to determine whether the nationally calibrated performance models used in the Mechanistic-Empirical Pavement Design Guide (MEPDG) provide a reasonable prediction of actual field performance, and if the desired accuracy or correspondence exists between predicted and monitored performance for Iowa conditions. A comprehensive literature review was conducted to identify the MEPDG input parameters and the MEPDG verification/calibration process. Sensitivities of MEPDG input parameters to predictions were studied using different versions of the MEPDG software. Based on literature review and sensitivity analysis, a detailed verification procedure was developed. A total of sixteen different types of pavement sections across Iowa, not used for national calibration in NCHRP 1-47A, were selected. A database of MEPDG inputs and the actual pavement performance measures for the selected pavement sites were prepared for verification. The accuracy of the MEPDG performance models for Iowa conditions was statistically evaluated. The verification testing showed promising results in terms of MEPDG’s performance prediction accuracy for Iowa conditions. Recalibrating the MEPDG performance models for Iowa conditions is recommended to improve the accuracy of predictions. ****************** Large File**************************

On performance persistence in emerging markets: Empirical evidence from Asia-Pacific

The purpose of this study is to investigate the performance persistence of international mutual funds, employing a data sample which includes 2,168 European mutual funds investing in Asia-Pacific region; Japan excluded. Also, a number of performance measures is tested and compared, and especially, this study tries to find out whether iterative Bayesian procedure can be used to provide more accurate predictions on future performance. Finally, this study examines whether the cross-section of mutual fund returns can be explained with simple accounting variables and market risk. To exclude the effect of the Asian currency crisis in 1997, the studied time period includes years from 1999 to 2007. The overall results showed significant performance persistence for repeating winners when performance was tested with contingency tables. Also the annualized alpha spreads between the top and bottom portfolios were more than ten percent at their highest. Nevertheless, the results do not confirm the improved prediction accuracy of the Bayesian alphas.

Does the Barro-Gordon Model Explain the Behavior of US Inflation? a Reexamination of the Empirical Evidence

This paper tests the predictions of the Barro-Gordon model using US data on inflation and unemployment. To that end, it constructs a general game-theoretical model with asymmetric preferences that nests the Barro-Gordon model and a version of Cukierman’s model as special cases. Likelihood Ratio tests indicate that the restriction imposed by the Barro-Gordon model is rejected by the data but the one imposed by the version of Cukierman’s model is not. Reduced-form estimates are consistent with the view that the Federal Reserve weights more heavily positive than negative unemployment deviations from the expected natural rate.

An event-based approach to validating solar wind speed predictions: high-speed enhancements in the Wang-Sheeley-Arge model

One of the primary goals of the Center for Integrated Space Weather Modeling (CISM) effort is to assess and improve prediction of the solar wind conditions in near‐Earth space, arising from both quasi‐steady and transient structures. We compare 8 years of L1 in situ observations to predictions of the solar wind speed made by the Wang‐Sheeley‐Arge (WSA) empirical model. The mean‐square error (MSE) between the observed and model predictions is used to reach a number of useful conclusions: there is no systematic lag in the WSA predictions, the MSE is found to be highest at solar minimum and lowest during the rise to solar maximum, and the optimal lead time for 1 AU solar wind speed predictions is found to be 3 days. However, MSE is shown to frequently be an inadequate “figure of merit” for assessing solar wind speed predictions. A complementary, event‐based analysis technique is developed in which high‐speed enhancements (HSEs) are systematically selected and associated from observed and model time series. WSA model is validated using comparisons of the number of hit, missed, and false HSEs, along with the timing and speed magnitude errors between the forecasted and observed events. Morphological differences between the different HSE populations are investigated to aid interpretation of the results and improvements to the model. Finally, by defining discrete events in the time series, model predictions from above and below the ecliptic plane can be used to estimate an uncertainty in the predicted HSE arrival times.

Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models

A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.