3 resultados para Multiple regression

em Indian Institute of Science - Bangalore - Índia


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Chital or axis deer (Axis axis) form fluid groups that change in size temporally and in relation to habitat. Predictions of hypotheses relating animal density, rainfall, habitat structure, and breeding seasonality, to changes in chital group size were assessed simultaneously using multiple regression models of monthly data collected over a 2 yr period in Guindy National Park, in southern India. Over 2,700 detections of chital groups were made during four seasons in three habitats (forest, scrubland and grassland). In scrubland and grassland, chital group size was positively related to animal density, which increased with rainfall. This suggests that in these habitats, chital density increases in relation to food availability, and group sizes increase due to higher encounter rate and fusion of groups. The density of chital in forest was inversely related to rainfall, but positively to the number of fruiting tree species and availability of fallen litter, their forage in this habitat. There was little change in mean group size in the forest, although chital density more than doubled during the dry season and summer. Dispersion of food items or the closed nature of the forest may preclude formation of larger groups. At low densities, group sizes in all three habitats were similar. Group sizes increased with chital density in scrubland and grassland, but more rapidly in the latter—leading to a positive relationship between openness and mean group size at higher densities. It is not clear, however, that this relationship is solely because of the influence of habitat structure. The rutting index (monthly percentage of adult males in hard antler) was positively related to mean group size in forest and scrubland, probably reflecting the increase in group size due to solitary males joining with females during the rut. The fission-fusion system of group formation in chital is thus interactively influenced by several factors. Aspects that need further study, such as interannual variability, are highlighted.

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Coastal lagoons are complex ecosystems exhibiting a high degree of non-linearity in the distribution and exchange of nutrients dissolved in the water column due to their spatio-temporal characteristics. This factor has a direct influence on the concentrations of chlorophyll-a, an indicator of the primary productivity in the water bodies as lakes and lagoons. Moreover the seasonal variability in the characteristics of large-scale basins further contributes to the uncertainties in the data on the physico-chemical and biological characteristics of the lagoons. Considering the above, modelling the distributions of the nutrients with respect to the chlorophyll-concentrations, hence requires an effective approach which will appropriately account for the non-linearity of the ecosystem as well as the uncertainties in the available data. In the present investigation, fuzzy logic was used to develop a new model of the primary production for Pulicat lagoon, Southeast coast of India. Multiple regression analysis revealed that the concentrations of chlorophyll-a in the lagoon was highly influenced by the dissolved concentrations of nitrate, nitrites and phosphorous to different extents over different seasons and years. A high degree of agreement was obtained between the actual field values and those predicted by the new fuzzy model (d = 0.881 to 0.788) for the years 2005 and 2006, illustrating the efficiency of the model in predicting the values of chlorophyll-a in the lagoon.

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This paper probes the role of internal factors in SMEs in obtaining external support and achieving innovation performance in the context of auto component, electronics and machine tool industries of Bangalore in India. Using step-wise logistic regression analysis, the study found that only if SMEs have internal technical competence in terms of technically qualified entrepreneur, an exclusive design centre, and innovate more frequently, they will be able to obtain external support. Further using step-wise multiple regression the study concluded that SMEs which have come up to implement innovative ideas or exploit market opportunities and which have obtained external support with technically qualified entrepreneurs are able to exhibit better innovation performance.