This study investigates fertilizer consumption patterns across 41 countries from 1961 to 2021. De... more This study investigates fertilizer consumption patterns across 41 countries from 1961 to 2021. Descriptive statistics reveal substantial variation in average fertilizer use (kg/hectare) and variability between countries. Statistical analyses confirm significant differences in consumption patterns, with fertilizer consumption identified as a major explanatory factor. Cluster analysis further differentiates countries into two groups based on their consumption levels. These findings highlight the need to consider fertilizer use within a country-specific context. Further research exploring the underlying factors driving these variations and their impact on crop yields could inform strategies for optimizing fertilizer use and promoting agricultural sustainability.
This paper aims to study the short-run and long-run cointegration relationships between the total... more This paper aims to study the short-run and long-run cointegration relationships between the total population, the cumulative number of new COVID-19-infected cases, and the cumulative number of deaths due to COVID-19 in different states in the US. The short-run relationship is assessed using the ARDL model, and the longrun relationship is assessed using the ARDL bounds test. To assess the consistency of the model parameters, the cumulative sum of recursive residuals test and the cumulative sum of recursive residuals squares tests are used.
The present investigation was carried out to study the food grain production trends in different ... more The present investigation was carried out to study the food grain production trends in different states in India based on Panel Regression Model for the period 2001-02 to 2020-2021. The results reveal that between state-to-state food grain production is highly significant the highest food grain production was registered in Uttar Pradesh followed by Punjab and Madhya Pradesh. Very lowest was registered in Kerala and Himachal Pradesh. The findings reveal that the highly significant fixed effect model was found to be suitable to study the trend and this model explains the 82% of variations in food grain production. Over all increasing in food grain production is noted.
The impacts of the coronavirus disease 2019 (COVID-19) pandemic have been extremely severe, with ... more The impacts of the coronavirus disease 2019 (COVID-19) pandemic have been extremely severe, with both economic and health crises experienced worldwide. The incidence of novel COVID-19 infections dramatically increased due to the absence of antiviral medications and vaccines, resulting in enormous economic losses, panic, and many deaths. Based on the panel regression model, this study examined the trends and correlations in the number of COVID-19-related deaths and the number of COVID-19-infected cases in all 37 regions of the Tamil Nadu state in India in August 2020. The fixed effects model had the most excellent R 2 value of 78% and exhibited significant results. The slope coefficient was also highly effective, showing a considerable variation in the relationship between new COVID-19 cases and deaths. Additionally, for every unit increase in COVID-19-infected instances, the death rate increased by 0.02%. The main issue with this model is that it did not differentiate between the various districts or inform us whether the overall COVID-19 mortality response to the explanatory variable over time was consistent across all neighborhoods.
This chapter proposes a new method for constructing binary and ternary variance balanced incomple... more This chapter proposes a new method for constructing binary and ternary variance balanced incomplete block designs based on the Kronecker product of two Hadamard matrices and unreduced symmetrical Balanced Incomplete Block Design. Method 1 discusses the construction of binary variance balanced block designs using the Kronecker product of two Hadamard matrices, and method 2 discusses the constructions of ternary variance balanced block design using the unreduced symmetrical, balanced incomplete block design with the parameters
This study employed multivariate statistical techniques to analyze soil nutrient data for crop cl... more This study employed multivariate statistical techniques to analyze soil nutrient data for crop classification, focusing on the "Potato" and "Raagi" crops. The analysis revealed highly significant differences in soil nutrient profiles between these crop types, with specific soil nutrients exhibiting substantial variability. The Fisher Linear Discriminant Analysis demonstrated exceptional discriminative power, achieving perfect crop separation. The confusion matrix indicated high classification accuracy, with "Potato" reaching 100% accuracy and "Ragi" at 96.15%. The ROC value of 0.992 further validated the model's effectiveness in crop discrimination. These findings highlight the utility of multivariate statistical approaches for crop classification and selection based on soil nutrient characteristics.
The main aim of this present chapter is to investigates the dynamic relationships between area an... more The main aim of this present chapter is to investigates the dynamic relationships between area and production of the wheat crop grown during 1989-90 to 2020-2021 in different districts of Gujarat state, India. Statistical analyses play a key role in current research studies on food security, where yield time series analysis is used to estimate past yield trends and to predict future yield trends. Various types of statistical models have been used for the analysis of yield time series. The time-series data on the area and production of wheat crops grown in different districts of Gujarat state from 1995-96 to 2019-2020 have been collected from the website. The Pedroni cointegration test indicates long-run equilibrium relationships between wheat area and yield, while the pairwise Granger causality test verifies cointegration linkages. The results reveal that the intercept and slopes are highly significant, and the model F-statistic is also highly significant, with a remarkably high R 2 of 92%. This model explains 92% of variations in wheat production. Additionally, for every unit increase in area under the wheat crop, the production is increased by 2.19 %. It is concluded that the long-term coefficient is positive and highly significant, indicating the existence of positive long-run equilibrium relationships between the study variables.
In this study, discriminant analysis techniques were employed to investigate the relationship bet... more In this study, discriminant analysis techniques were employed to investigate the relationship between sandy soil categories and macronutrients. The assumptions of linear discriminant function analysis such as the normality of regressors, multicollinearity, Homoscedasticity were carefully examined. The data were transformed using the Box-Cox method to improve normality, and a multivariate analysis of variance was employed to determine whether there were significant differences in soil macronutrients between the sand groups. The results showed that there were significant differences in soil macronutrients between the sand groups, and the classification accuracy of the discriminant function was 67%. The findings suggested that the discriminant function analysis could be used for classifying soil types based on their macronutrient content, particularly in sandy soil.
Background and Objective: The novel coronavirus pandemic, known as COVID-19, could not have been ... more Background and Objective: The novel coronavirus pandemic, known as COVID-19, could not have been more predictable; thus, the world encountered health crises and substantial economic crises. This paper analysed the trends in COVID-19 cases in October 2020 in four southern districts of Tamil Nadu state, India, using a panel regression model. Materials and Methods: Panel data on the number of COVID-19-infected cases were collected from daily bulletins published through the official website www.stopcorona.tn.gov.in maintained by the Government of Tamil Nadu state, India. Panel data regression models were employed to study the trends. EViews Ver.11. Software was used to estimate the model and its parameters. Results: In all four districts, the COVID-19-infected case data followed a normal distribution. Maximum numbers of COVID-19-infected cases were registered in Kanniyakumari, followed by Tirunelveli, Thoothukudi and Tenkasi districts. The fewest COVID-19 cases were registered in Tenkas...
International Journal of Modern Agriculture, Volume 10, No.2, 2021 ISSN: 2305-7246, 2021
An empirical investigation was carried out to study the variation in five soil data, including po... more An empirical investigation was carried out to study the variation in five soil data, including potential of Hydrogen, Electrical Conductivity, Organic Carbon, available Phosphorus, and Potassium. The data on these five soil parameters pertaining to 47 villages of Palayamkottai taluka in the district of Tirunelveli, Tamil Nadu State, INDIA were obtained from the Soil Health Card scheme. These soil parameters were subjected to various statistical analyses. An analysis of variance showed that variations in different soil parameters among the villages were highly significant; that is, these individual parameters were significantly different across the villages. A multivariate analysis of variance test revealed a significant variation between the villages when all the five soil parameters were considered simultaneously. Through all the soil parameters were found to be significant both individually and together, the clustered variation was largely due to variations in Organic Carbon, Electrical Conductivity, and Phosphorus as confirmed by Ward's method. Three clusters were identified such that there was homogeneity within the clusters and heterogeneity between the clusters.
The present investigation was carried out to study the trends in COVID-19 infected cases and deat... more The present investigation was carried out to study the trends in COVID-19 infected cases and deaths based on the parametric, exponential smoothing and non-parametric regression models by using COVID-19 cumulative infected cases and deaths due to infections The statistically most suited parametric models are selected based on the highest adjusted R2, significant regression co-efficient and co-efficient of determination (R2). Appropriate model is selected based on the model performance measures such as, Root Mean Square Error, Mean Absolute Error, Mean Absolute Percentage Error, assumptions of normality and independence of residuals. Nonparametric estimates of underlying growth functions are computed at each and every time points.
The present investigation was carried out to study area production trends of Paddy crop grown in ... more The present investigation was carried out to study area production trends of Paddy crop grown in different districts of Tamil Nadu state, India during the period 1998-99 to 2010-2020 based on Panel Regression Model. The statistically most suited Panel Regression model was selected based on Hausman and Wald test. The study variables namely the area under the Paddy crop (AREA) and the production (PRODN) of Paddy crop were found to be stationary at level. Analysis of variance test indicated that district to district crop productions were highly significant. Highest area under the crops and productions were registered in Tiruvarur, Thanjavur etc., Very lowest were registered in Coimbatore and Nilgiris districts. The fixed effect model was found to be suitable to study the trend and this model explains the 87% of variations in Paddy crop production.
This chapter discuss the new method of constructing Optimal Super Saturated design based on 3 n-f... more This chapter discuss the new method of constructing Optimal Super Saturated design based on 3 n-factorial design by merging some of the treatment combinations, deleting control and some other unimportant treatment combinations in 3 n-factorial design. Also the to find the efficiency of the constructed design and to find the it's lower bound value.
This study investigates fertilizer consumption patterns across 41 countries from 1961 to 2021. De... more This study investigates fertilizer consumption patterns across 41 countries from 1961 to 2021. Descriptive statistics reveal substantial variation in average fertilizer use (kg/hectare) and variability between countries. Statistical analyses confirm significant differences in consumption patterns, with fertilizer consumption identified as a major explanatory factor. Cluster analysis further differentiates countries into two groups based on their consumption levels. These findings highlight the need to consider fertilizer use within a country-specific context. Further research exploring the underlying factors driving these variations and their impact on crop yields could inform strategies for optimizing fertilizer use and promoting agricultural sustainability.
This paper aims to study the short-run and long-run cointegration relationships between the total... more This paper aims to study the short-run and long-run cointegration relationships between the total population, the cumulative number of new COVID-19-infected cases, and the cumulative number of deaths due to COVID-19 in different states in the US. The short-run relationship is assessed using the ARDL model, and the longrun relationship is assessed using the ARDL bounds test. To assess the consistency of the model parameters, the cumulative sum of recursive residuals test and the cumulative sum of recursive residuals squares tests are used.
The present investigation was carried out to study the food grain production trends in different ... more The present investigation was carried out to study the food grain production trends in different states in India based on Panel Regression Model for the period 2001-02 to 2020-2021. The results reveal that between state-to-state food grain production is highly significant the highest food grain production was registered in Uttar Pradesh followed by Punjab and Madhya Pradesh. Very lowest was registered in Kerala and Himachal Pradesh. The findings reveal that the highly significant fixed effect model was found to be suitable to study the trend and this model explains the 82% of variations in food grain production. Over all increasing in food grain production is noted.
The impacts of the coronavirus disease 2019 (COVID-19) pandemic have been extremely severe, with ... more The impacts of the coronavirus disease 2019 (COVID-19) pandemic have been extremely severe, with both economic and health crises experienced worldwide. The incidence of novel COVID-19 infections dramatically increased due to the absence of antiviral medications and vaccines, resulting in enormous economic losses, panic, and many deaths. Based on the panel regression model, this study examined the trends and correlations in the number of COVID-19-related deaths and the number of COVID-19-infected cases in all 37 regions of the Tamil Nadu state in India in August 2020. The fixed effects model had the most excellent R 2 value of 78% and exhibited significant results. The slope coefficient was also highly effective, showing a considerable variation in the relationship between new COVID-19 cases and deaths. Additionally, for every unit increase in COVID-19-infected instances, the death rate increased by 0.02%. The main issue with this model is that it did not differentiate between the various districts or inform us whether the overall COVID-19 mortality response to the explanatory variable over time was consistent across all neighborhoods.
This chapter proposes a new method for constructing binary and ternary variance balanced incomple... more This chapter proposes a new method for constructing binary and ternary variance balanced incomplete block designs based on the Kronecker product of two Hadamard matrices and unreduced symmetrical Balanced Incomplete Block Design. Method 1 discusses the construction of binary variance balanced block designs using the Kronecker product of two Hadamard matrices, and method 2 discusses the constructions of ternary variance balanced block design using the unreduced symmetrical, balanced incomplete block design with the parameters
This study employed multivariate statistical techniques to analyze soil nutrient data for crop cl... more This study employed multivariate statistical techniques to analyze soil nutrient data for crop classification, focusing on the "Potato" and "Raagi" crops. The analysis revealed highly significant differences in soil nutrient profiles between these crop types, with specific soil nutrients exhibiting substantial variability. The Fisher Linear Discriminant Analysis demonstrated exceptional discriminative power, achieving perfect crop separation. The confusion matrix indicated high classification accuracy, with "Potato" reaching 100% accuracy and "Ragi" at 96.15%. The ROC value of 0.992 further validated the model's effectiveness in crop discrimination. These findings highlight the utility of multivariate statistical approaches for crop classification and selection based on soil nutrient characteristics.
The main aim of this present chapter is to investigates the dynamic relationships between area an... more The main aim of this present chapter is to investigates the dynamic relationships between area and production of the wheat crop grown during 1989-90 to 2020-2021 in different districts of Gujarat state, India. Statistical analyses play a key role in current research studies on food security, where yield time series analysis is used to estimate past yield trends and to predict future yield trends. Various types of statistical models have been used for the analysis of yield time series. The time-series data on the area and production of wheat crops grown in different districts of Gujarat state from 1995-96 to 2019-2020 have been collected from the website. The Pedroni cointegration test indicates long-run equilibrium relationships between wheat area and yield, while the pairwise Granger causality test verifies cointegration linkages. The results reveal that the intercept and slopes are highly significant, and the model F-statistic is also highly significant, with a remarkably high R 2 of 92%. This model explains 92% of variations in wheat production. Additionally, for every unit increase in area under the wheat crop, the production is increased by 2.19 %. It is concluded that the long-term coefficient is positive and highly significant, indicating the existence of positive long-run equilibrium relationships between the study variables.
In this study, discriminant analysis techniques were employed to investigate the relationship bet... more In this study, discriminant analysis techniques were employed to investigate the relationship between sandy soil categories and macronutrients. The assumptions of linear discriminant function analysis such as the normality of regressors, multicollinearity, Homoscedasticity were carefully examined. The data were transformed using the Box-Cox method to improve normality, and a multivariate analysis of variance was employed to determine whether there were significant differences in soil macronutrients between the sand groups. The results showed that there were significant differences in soil macronutrients between the sand groups, and the classification accuracy of the discriminant function was 67%. The findings suggested that the discriminant function analysis could be used for classifying soil types based on their macronutrient content, particularly in sandy soil.
Background and Objective: The novel coronavirus pandemic, known as COVID-19, could not have been ... more Background and Objective: The novel coronavirus pandemic, known as COVID-19, could not have been more predictable; thus, the world encountered health crises and substantial economic crises. This paper analysed the trends in COVID-19 cases in October 2020 in four southern districts of Tamil Nadu state, India, using a panel regression model. Materials and Methods: Panel data on the number of COVID-19-infected cases were collected from daily bulletins published through the official website www.stopcorona.tn.gov.in maintained by the Government of Tamil Nadu state, India. Panel data regression models were employed to study the trends. EViews Ver.11. Software was used to estimate the model and its parameters. Results: In all four districts, the COVID-19-infected case data followed a normal distribution. Maximum numbers of COVID-19-infected cases were registered in Kanniyakumari, followed by Tirunelveli, Thoothukudi and Tenkasi districts. The fewest COVID-19 cases were registered in Tenkas...
International Journal of Modern Agriculture, Volume 10, No.2, 2021 ISSN: 2305-7246, 2021
An empirical investigation was carried out to study the variation in five soil data, including po... more An empirical investigation was carried out to study the variation in five soil data, including potential of Hydrogen, Electrical Conductivity, Organic Carbon, available Phosphorus, and Potassium. The data on these five soil parameters pertaining to 47 villages of Palayamkottai taluka in the district of Tirunelveli, Tamil Nadu State, INDIA were obtained from the Soil Health Card scheme. These soil parameters were subjected to various statistical analyses. An analysis of variance showed that variations in different soil parameters among the villages were highly significant; that is, these individual parameters were significantly different across the villages. A multivariate analysis of variance test revealed a significant variation between the villages when all the five soil parameters were considered simultaneously. Through all the soil parameters were found to be significant both individually and together, the clustered variation was largely due to variations in Organic Carbon, Electrical Conductivity, and Phosphorus as confirmed by Ward's method. Three clusters were identified such that there was homogeneity within the clusters and heterogeneity between the clusters.
The present investigation was carried out to study the trends in COVID-19 infected cases and deat... more The present investigation was carried out to study the trends in COVID-19 infected cases and deaths based on the parametric, exponential smoothing and non-parametric regression models by using COVID-19 cumulative infected cases and deaths due to infections The statistically most suited parametric models are selected based on the highest adjusted R2, significant regression co-efficient and co-efficient of determination (R2). Appropriate model is selected based on the model performance measures such as, Root Mean Square Error, Mean Absolute Error, Mean Absolute Percentage Error, assumptions of normality and independence of residuals. Nonparametric estimates of underlying growth functions are computed at each and every time points.
The present investigation was carried out to study area production trends of Paddy crop grown in ... more The present investigation was carried out to study area production trends of Paddy crop grown in different districts of Tamil Nadu state, India during the period 1998-99 to 2010-2020 based on Panel Regression Model. The statistically most suited Panel Regression model was selected based on Hausman and Wald test. The study variables namely the area under the Paddy crop (AREA) and the production (PRODN) of Paddy crop were found to be stationary at level. Analysis of variance test indicated that district to district crop productions were highly significant. Highest area under the crops and productions were registered in Tiruvarur, Thanjavur etc., Very lowest were registered in Coimbatore and Nilgiris districts. The fixed effect model was found to be suitable to study the trend and this model explains the 87% of variations in Paddy crop production.
This chapter discuss the new method of constructing Optimal Super Saturated design based on 3 n-f... more This chapter discuss the new method of constructing Optimal Super Saturated design based on 3 n-factorial design by merging some of the treatment combinations, deleting control and some other unimportant treatment combinations in 3 n-factorial design. Also the to find the efficiency of the constructed design and to find the it's lower bound value.
Uploads
Papers by Rajarathinam A
Books by Rajarathinam A