Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Comparing finite state machine test coverage criteria

To plan testing activities, testers face the challenge of determining a strategy, including a test coverage criterion that offers an acceptable compromise between the available resources and test goals. Known theoretical properties of coverage criteria do not always help and, thus, empirical data are needed. The results of an experimental evaluation of several coverage criteria for finite state machines (FSMs) are presented, namely, state and transition coverage; initialisation fault and transition fault coverage. The first two criteria focus on FSM structure, whereas the other two on potential faults in FSM implementations. The authors elaborate a comparison approach that includes random generation of FSM, construction of an adequate test suite and test minimisation for each criterion to ensure that tests are obtained in a uniform way. The last step uses an improved greedy algorithm.

Dentin hypersensitivity clinical study comparing LILT and LEDT keeping the same irradiation parameters

Dentin hypersensitivity is a common condition associated with high dental pain. A new LED-based (light emitting diode) light source has been used as an experimental tool in some studies. Purpose: The main objective was to compare these two light sources emitting in the same spectral band (red from 625 to 660 nm) to promote pain relief. Material and methods: A total of 6 sessions were accomplished, being three irradiation sessions and three follow-up sessions. This single-blind study compared a control group (Placebo) and two other groups with different equipments: low laser intensity treatment (LILT) and a light emitting diode system treatment (LEDT). Results: The results showed that there is no statistical difference between LILT and LEDT groups, however, both were better than control group (p=0.01) in terms of treatment efficiency; there is no difference between the second and the third sessions for both treatment, it means that the third session was not necessary; finally, the improvement at the end of the entire research (follow up care of 30 days) was very expressive in comparison to pre-treatment situation for all teeth (p=0.01). Conclusion: LILT and LEDT were equally effective to treat dentine hypersensitivity, a 3rd treatment session was not necessary/two sessions are enough.

Comparing time-varying autoregressive structures of locally stationary processes

In this paper, a novel statistical test is introduced to compare two locally stationary time series. The proposed approach is a Wald test considering time-varying autoregressive modeling and function projections in adequate spaces. The covariance structure of the innovations may be also time- varying. In order to obtain function estimators for the time- varying autoregressive parameters, we consider function expansions in splines and wavelet bases. Simulation studies provide evidence that the proposed test has a good performance. We also assess its usefulness when applied to a financial time series.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Urea amperometric biosensors based on a multifunctional bipolymeric layer: Comparing enzyme immobilization methods

This paper outlines the results obtained with biosensors designed for urea amperometric detection. The incorporation of urease into a bipolymeric substrate consisting of poly(pyrrole) and poly(5-amino-1-naphthol) was performed through four different approaches: direct adsorption, entrapment in cellulose acetate layer. cross-linking with glutaraldehyde, and also covalent attachment to the polymeric matrix. Poly(pyrrole) acts as amperometric transducer in these biosensors, while poly(5-amino-1-naphthol) drastically reduces the interference signal of agents such as ascorbic and uric acids. The biosensors containing urease covalently attached to the substrate provided interesting results in terms of sensitivity towards urea (0.50 mu A cm(-2) mmol(-1) L), lifetime (20 days) and short response times, due to the enzyme immobilization method used. All biosensors analyzed showed also a wide linear concentration range (up to 100 mmol L(-1)) and low detection limits (0.22-0.58 mmol L(-1)). (C) 2009 Elsevier B.V. All rights reserved.

The Relationship between Transport Infrastructure and EconomicGrowth: An Empirical Analysis Comparing Developing and DevelopedCountries

Gross domestic product (GDP) is generally considered as the most important index and comprehensive measure of the size of economy. This paper investigates empirically the relationship between transport infrastructure (focus on highways) and GDP growth based on a production function approach. The physical stocks of transport infrastructure were used instead of monetary data to measure public capital together with several other variables (labor and private capital) that were hypothesized to affect economic growth. Then we explore a number of subsequent studies that use panel data covering the period between 1992 and 2004. An investigation was done to compare developed countries and developing countries. Results indicate that physical units are positively and significantly related to economic growth. Furthermore there was an interesting finding that the output elasticity with respect to physical units for developed countries is higher than developing countries.

Comparing two multivariate unit root tests

In this essay, a method for comparing the asymptotic power of the multivariate unit root tests proposed in Phillips & Durlauf (1986) and Flˆores, Preumont & Szafarz (1996) is proposed. In order to determine the asymptotic power of the tests the asymptotic distributions under the null hypothesis and under the set of alternative hypotheses described in Phillips (1988) are determined. In addition, a test which combines characteristics of both tests is proposed and its distributions under the null hypothesis and the same set of alternative hypotheses are determined. This allows us to determine what causes any difference in the asymptotic power of the two tests against the set of alternative hypotheses considered

Comparing value-at-risk methodologies

In this paper, we compare four different Value-at-Risk (V aR) methodologies through Monte Carlo experiments. Our results indicate that the method based on quantile regression with ARCH effect dominates other methods that require distributional assumption. In particular, we show that the non-robust methodologies have higher probability to predict V aRs with too many violations. We illustrate our findings with an empirical exercise in which we estimate V aR for returns of S˜ao Paulo stock exchange index, IBOVESPA, during periods of market turmoil. Our results indicate that the robust method based on quantile regression presents the least number of violations.

Comparing equilibrium real interest rates : different approaches to measure Brazilian rates

Despite the difficulties involved in the precise determination of equilibrium real interest rates, it seems clear that nominal interest rates has been higher in Brazil than in similar emerging economies. This paper aims to shed light on the possible reasons for this feature of the Brazilian economy. We extend Miranda and Muinhos (2003) one-country study to a sample of 20 countries, using many methods to compare measures of the real interest: (i) extracting equilibrium interest rates from IS curves; (ii) extracting steady state interest rates from marginal product of capital; (iii) capturing relevant variables and the fixed effects having real interest rates as dependent variable in a panel for emerging countries; and (iv) extracting inflation expectation from the spread between fixed rate and inflation-indexed treasure notes.

Leader-organization fit: comparing the effectiveness of paternalistic and transformational leadership in different organizational cultures

Research on paternalistic leadership (PL) has been based exclusively on national cultures´ differences. However there are cues that other contextual variables can add to the explanation of this construct. Due to its capacity to influence expectations of individuals in organizations, organizational culture can contribute to fill this gap. To test if organizational culture influences the effectiveness of leadership style, we conducted two experimental studies using Amazon’s Mechanical Turk, comparing effects of paternalistic and transformational leadership on followers’ outcomes. Using video clips and vignettes, we found that PL is better related to followers´ outcomes in cultures oriented to people than outcome, and that TL has a better relationship in cultures oriented to innovation than stability. The results suggest that organizational culture helps in explaining PL endorsement, and that further analysis of the influence of this variable to PL can provide a better understanding of the expression of this leadership style in organizations.