Gutierrez et al. (2005) studied Gompertz homogeneous diffusion process with exogenous variables that affect the trend. The purpose of present article is to modify this work in two directions. The first one is that the diffusion term is taken as time-dependent, which is more realistic. Another direction of modification is that the powerful technique of Wavelet analysis is employed to estimate the drift term, rather than the elementary piecewise time-varying linear functions approach. The methodology, after incorporating the above two aspects is developed. Relevant computer programs for its application are written and the same are included as an Appendix. Finally, as an illustration, India?s total foodgrain production time-series data dependent on rainfall, fertilizer, and pesticide time-series data as exogenous variables are considered and superiority of our proposed model is shown over the model proposed by Gutierrez et al. (2005) for given data. Keywords: Gompertz nonlinear growth model, Stochastic differential equation, Time-dependent diffusion, Wavelet analysis.

  This paper deals with obtaining series of block designs for complete and partial diallel cross experiments balanced for neighbour effects. Two series of Neighbour Balanced Block (NBB) designs for diallel cross in complete blocks and two series of NBB for diallel cross in incomplete blocks have been obtained. A catalogue of designs for number of lines ? 20 has been prepared listing the parameters of the designs. Keywords: Diallel cross, Neighbour effects, General combining ability, Specific combining ability, Variance balanced.

  Trend analysis of rainfall has been of great concern during the past century as well as today because of the consideration has been given to global climate change by the scientific community. The study of trends is very important for a country like India whose food security and economy are dependent on the timely availability of water such as 83% water used for agriculture sector, 12% for industrial sector and only 5% for domestic sector(source: MoWR, GOI, 2015-16). So the present study attempted to know the trend of rainfall and rainy days of Sehore district of Madhya Pradesh for the period (1992-2016). The change point analysis has been analyzed for observing any change. For this purpose, rainfall data have been collected from five meteorological stations of Sehore, Astha, Ichhawar, Budhni and Nasrullaganj.Trends of rainfall parameters were analyzed using Mann-Kendall test, Sen?s slope test, Spearman?s rho test and regression and change point analysis. This study revealed that significant decreasing trend in annual, monsoon and September rainfall have been observed at Sehore, whereas May shows increasing trend of rainfall. Though, rainfall in the month of May has increased significantly at 5% level of significance but there is no significant trend in rainy days. For the period 1992-2016, Pettitt change point analysis revealed that there is no significant change in rainfall and rainy days. The main aim of this study is to provide detailed knowledge of the rainfall regime in a smaller area such as district level is an important prerequisite for agricultural planning and management, for this one should go for micro level climate data analysis. Keywords: Mann-Kendall test, Pettitt change point analysis, Sen?s slope, Spearman?s rho test.

  The vector autoregressive (VAR) models are being widely used for modeling and forecasting multiple time series. But the problem of over parameterization has restricted their use only for small number of time series. The Constrained VAR, Bayesian VAR and Least Absolute Shrinkage and Selection Operator (LASSO) applied for VAR to shrink the parameter estimates have gain importance in this regard. The present study is directed at empirically comparing the performance of Constrained VAR, Bayesian VAR and LASSO VAR using the data on annual estimated landings of six different marine fish species in India. The results from the forecast evaluation techniques indicated that all three techniques are equally good in forecasting the estimated fish landings whereas LASSO VAR outperformed Bayesian VAR in shrinking the parameters of the model to zero. Keywords: Bayesian VAR, LASSO, Over parameterization, Shrinkage.

  One of the most important challenges facing Indian agriculture is to provide food & nutritional security for rural resource-poor communities in the wake of decreasing land holdings. Hence, selection of suitable cultivar or variety for specific environment is very much essential. The farmer?s risk can be minimized and it may improve their economic condition through selection of stable genotypes by using a suitable stability measure. Evaluation can be minimized and it may improve their economic condition through selection of stable genotypes by using a suitable stability measure. Evaluation of genotypes on the basis of stability measure is essential for yield trials in different environments. Though, large numbers of stability measures are available in literature, but deciding the proper stability measure for selecting stable genotypes is problematic. Multiple Criteria Decision-Making (MCDM) technique or Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been employed to develop the proposed measure. In the present study, a suitable composite measure is developed by combining several methods into a single aggregate method by using MCDM technique, for selecting suitable genotypes which would be stable to environmental variations. Keywords: Genotype × Environment interaction, Huehn?s nonparametric measures, MCDM technique, Multi-Environment trial, Randomized complete block design, Stability measures, TOPSIS, Wricke?s ecovalence.

  The present study considered zero and first order reaction models with equi- and auto- correlated error structures for predicting the accelerated shelf life of chill stored fish. The parameters estimated using these models were used to compute Q- the accelerated shelf life prediction quotient. The models with auto- correlated errors were fitted to two real time data obtained from the storage study of Milk fish (chanos chanos) and Tilapia (Oreochromis mossambicus) at 0 -2 0 EBC. The temperature behavior on the quality responses for two species of fish was examined as a case study by combining the effect of storage time and temperature using parametric zero and first order reactions models. Keywords: Zero and first order reaction models, Accelerated shelf life prediction, Equi-and auto-correlated errors, Milk fish (chanos chanos), Tilapia (Oreochromis mossambicus), Combined models. Warner (1965) introduced the randomized response (RR) techniques for the collection of data relating to sensitive characteristics. Kuk (1990) proposed a modified RR technique which is more efficient than Warner?s (1965) RR technique. In this paper an alternative RR technique is proposed which is more efficient than the Kuk?s (1990) RR technique. Keywords: Inclusion probabilities, Randomized response, Sampling design.

  Warner (1965) introduced the randomized response (RR) techniques for the collection of data relating to sensitive characteristics. Kuk (1990) proposed a modified RR technique which is more efficient than Warner?s (1965) RR technique. In this paper an alternative RR technique is proposed which is more efficient than the Kuk?s (1990) RR technique. Keywords: Inclusion probabilities, Randomized response, Sampling design.

  This paper is an attempt to analyze the effect of modified Hansen and Hurwitz (1946) technique to estimate the current population mean in case of quantitative sensitive variable in two-occasion successive sampling. The problem of evaluating the degree of privacy protection is also considered. Randomized linear model and their special cases have been considered on current occasion and properties of the proposed estimation strategy have been examined. Simulation studies are carried out to evaluate the performances of the proposed estimator with respect to estimators under (i) complete response and(ii) under Hansen and Hurwitz (1946) technique. Analytical and numerical comparisons of some well-known scrambled models have been carried out in terms of efficiency and privacy protection. Results have proved the effectiveness of the suggested estimation strategy in real life situations. Keywords: Non-response, Successive sampling, Variance, Scrambled response, Privacy protection.

  The importance of reliability theory has grown out of the demands of modern technology and particularly out of the experiences complex military systems. The present investigation focus on importance of application of Weibull distribution in reliability theory as it is frequently used based on the assumption of a special type of non-homogeneous Poisson process. Also discussed some of the important inferential statistics of Weibull process in application to reliability theory. Keywords: Reliability theory, Weibull distribution, Compound distribution, Maximum likelihood estimation, Confidence interval.

  Agriculture is the backbone of India and data is a driver of growth and change. In agriculture domain also, large amount of data is being collected Agriculture is the backbone of India and data is a driver of growth and change. In agriculture domain also, large amount of data is being collected Agriculture is the backbone of India and data is a driver of growth and change. In agriculture domain also, large amount of data is being collected by various agencies including Government of India. The data is generated every day at various levels namely household, village, district, state and country. Data collection is done and recorded at current status regarding spatial boundaries of the units. At country level, there is no change in the boundary. State level spatial changes are rare and easy to capture in the data analysis. But, district level temporal data analysis creates problem because of the variation in number of districts and changes in their areas over a period of time. Thus, temporal data at district level requires adjustment called apportioning before analysis. These adjustment in data vary from variable to variable. The paper discusses apportioning methodology for different categories of variables using mathematical notations as well as using software named DAS developed for this purpose. The software has been developed using the programming language C# and tested using different datasets. The software called DAS (http://das.iasri.res.in) has been developed and also made available online. Keywords: Apportioning, DAS, District boundaries, Web based and district data.

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