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Global annual average temperature – a precise modelling

100%
Pal S., Ghosh A.
Biometrical Letters
|
2014
|
tom 51
|
nr 1
37-44
EN
Global annual average temperature (GAAT) is regarded as a precise indicator of the warming of the globe over the centuries, and its spectre is looming large with the passage of time and with the advancement of civilization. Global warming, caused by the accumulation of greenhouse gases in the atmosphere, has become the worst environmental threat to mankind. The phase 1981 to 2012 was the most crucial phase, and the impact of global warming in that phase indeed points to a disaster if not controlled now. Work on the building of appropriate models to represent the GAAT data can be found in the literature, although the precision levels (in terms of R2 values) of such models do not exceed 0.86. In this paper, six models are developed by using different combinations of mathematical functions. The developed models are superior to existing models in terms of their precision. In fact, to generate such models, extensive simulation work has been carried out not only with respect to the types of mathematical functions, but also with respect to the choices of initial values of the coefficients involved in each model. The models developed here have attained R2 values as high as 0.896.
2
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On determination of ETL – a distributional approach

81%
Pal S., Ghosh A., Dhar T.
Biometrical Letters
|
2013
|
tom 50
|
nr 2
107-116
EN
Economic threshold level (ETL) is an important component in pest management and control. Usually, it is determined by the grower/technologist utilizing his experience on a crop; however, for cereals the values of these indices are available. Knowledge of ETL helps reduce crop loss (and ensure less pesticide application), and as a consequence, profit is increased. Also substantial knowledge is required on the dynamics of the pest population, in order to determine the density at which the economic injury level (EIL) may be prevented (Weersink et al. 1991). This paper is devoted to the development of an analytical method (probabilistic) for determination of ETL, which is defined as the density at which control measures should be determined to prevent an increasing pest population from reaching the economic injury level. A method to model the dynamics of the pest population is also proposed. The above method is demonstrated on a real life data set on pest (whitefly) incidence on betelvine, obtained from an experiment designed for that purpose.
3
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Determination of robust optimum plot size and shape – a model-based approach

81%
Pal S., Mandal G., Dihidar K.
Biometrical Letters
|
2015
|
tom 52
|
nr 1
13-22
EN
Determination of optimum plot size has been regarded as an important and useful area of study for agriculturists and statisticians since the first remarkable contribution on this problem came to light in a paper by Smith (1938). As we explore the scientific literature relating to this problem, we may note a number of contributions, including those of Modjeska and Rawlings (1983), Webster and Burgess (1984), Sethi (1985), Zhang et al. (1990, 1994), Bhatti et al.(1991), Fagroud and Meirvenne (2002), etc. In Pal et al. (2007), a general method was presented by means of which the optimum plot size can be determined through a systematic analytical procedure. The importance of the procedure stems from the fact that even with Fisherian blocking, the correlation among the residuals is not eliminated (as such the residuals remain correlated). The method is based on an application of an empirical variogram constructed on real-life data sets (obtained from uniformity trials) wherein the data are serially correlated. This paper presents a deep and extensive investigation (involving theoretical exploration of the effect of different plot sizes and shapes in discovering the point – actually the minimum radius of curvature of the variogram at that point – beyond which the theoretical variogram assumes stationary values with further increase in lags) in the case of the most commonly employed model (incorporating a correlation structure) assumed to represent real-life data situations (uniformity trial or designed experiments, RBD/LSD).
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