Bishal Gurung - Academia.edu (original) (raw)

Papers by Bishal Gurung

Research paper thumbnail of Price volatility spillover of Indian onion markets: A comparative study

The Indian Journal of Agricultural Sciences

To investigate the interdependence between Indian onion markets in terms of price volatility, the... more To investigate the interdependence between Indian onion markets in terms of price volatility, the present study was conducted in four different vital onion markets in India, viz. Mumbai, Nashik, Delhi and Bengaluru. The long term monthly data, from March, 2003 to September, 2015 was collected from the website of agmarknet.nic.in. We have employed the VEC-MGARCH model to estimate mean and volatility spillover simultaneously among the different markets and also examined the nature of dynamic correlation using the DCC model. The presence of mean and volatility spillover was found between the markets. This type of significant interaction between the volatility of different markets is highly useful for cross market hedging and for sharing of common information by market participants. The empirical results also suggest for a very close observation on different market behavioral pattern since, “news” in one market may impact other market through the number of interdependencies. Key words: ...

Research paper thumbnail of Stochastic volatility in mean model for capturing the conditional variance in volatile time series data

The Indian Journal of Agricultural Sciences

Research paper thumbnail of Forecasting of crop yield using weather parameters - two step nonlinear regression model approach

The Indian Journal of Agricultural Sciences

Concept of the paper is firstly to remove the trend of crop yield and then to develop the forecas... more Concept of the paper is firstly to remove the trend of crop yield and then to develop the forecasting models using detrended yield. Not much work is available or development of forecast models or modelling due to their non-linear behaviour. For that, in this paper, methodology developed for forecasting using nonlinear growth models, which will help in forecasting yield, pest and disease incidences etc with high accuracy. Crop yield forecast models for wheat crop have been developed (using non-linear growth models, linear models and weather indices approach with weekly weather data) for different districts of Uttar Pradesh (UP). Weather Indices (WI) were obtained using above two approaches. Weather indices based regression models were developed using weather indices as independent variables while character under study such as crop yield was used as dependent variable for wheat crop, i.e. two step non-linear forecast model. Technique of forecasting using non-linear approach and using ...

Research paper thumbnail of Performance evaluation of yield crop forecasting models using weather index regression analysis

The Indian Journal of Agricultural Sciences

A crop forecast is a statement of the most likely magnitude of yield or production of a crop. It ... more A crop forecast is a statement of the most likely magnitude of yield or production of a crop. It is made on the basis of known facts on a given date and it assumes that the weather conditions and damages during the remainder of the growing season will be about the same as the average of previous year. The present paper deals with use of non-linear regression analysis for developing wheat yield forecast model for Allahabad district (India). A novel statistical approach attempted in this study to use nonlinear models with different weather variables and their indices and compare them to identify a suitable forecasting model. Time series yield data of 40 years (1970-2010) and weather data for the year 1970-71 to 2009-10 have been utilized. The models have been used to forecast yield in the subsequent three years 2008-09 to 2009-10 (which were not included in model development). The approach provided reliable yield forecast about two months before harvest.

Research paper thumbnail of Wheat yield forecast using detrended yield over a sub-humid climatic environment in five districts of Uttar Pradesh, India

The Indian Journal of Agricultural Sciences

A study was carried out to forecast the yield of the wheat crop for five districts of Uttar Prade... more A study was carried out to forecast the yield of the wheat crop for five districts of Uttar Pradesh namely Lucknow, Kanpur, Banda, Jhansi and Faizabad. The daily weather data on variables such as maximum temperature, rainfall, minimum temperature, and relative humidity were arranged week wise from sowing to harvesting and the relations between the weather variables and yield was worked out using statistical tools like correlation and regression. The yield has been detrended by obtaining the parameter estimates of the model and subsequently the detrended yield was used to forecast the yield of the crop using ARIMA model. The proposed method of obtaining pre-harvest forecasting of yield of crops was compared with the traditional approaches of forecasting and the proposed method was evaluated in terms of criteria's such as goodness of fit of the model. It was observed that in all the districts the proposed model performed better as compared to the traditional method both in terms o...

Research paper thumbnail of Pre harvest forecasting of crop yield using non-linear regression modelling: A concept

The Indian Journal of Agricultural Sciences

The concept of pre-harvesting of crop yield using nonlinear growth models and detrended yield for... more The concept of pre-harvesting of crop yield using nonlinear growth models and detrended yield for developing yield forecast model is rarely employed in forecasting. A novel approach attempted in this study to use nonlinear models with different weather variables and their indices and compare them to identify a suitable forecasting model. Weather indices based regression models were developed using weather indices as independent variables whiledetrended yield (residuals) was considered as dependent variable. The approach provided reliable yield forecastabout two months before harvest.

Research paper thumbnail of Forecasting crop yield through weather indices through LASSO

The Indian Journal of Agricultural Sciences

Reliable forecast of crop production before the harvest is important for advance planning, formul... more Reliable forecast of crop production before the harvest is important for advance planning, formulation and implementation policies dealing with food procurement, its distribution, pricing structure, import and export decisions, and storage and marketing of the agricultural commodities. Weather plays a very important role in crop growth and development. Therefore, model based on weather variables can provide reliable forecast. Weather variables used can be employed for crop production forecast by making appropriate models. In this study, a statistical model is used for crop yield forecast at different growth stages of wheat crop. This model uses maximum and minimum temperature, rainfall, morning and evening relative humidity during crop growing period. The forecast model was developed using generated weather indices as regressors in model. In order to select significant weather variables affecting the yield of crop least absolute shrinkage and selection operator (LASSO) as well as st...

Research paper thumbnail of Growth and diffusion dynamics of tractor in Punjab

The Indian Journal of Agricultural Sciences

Over the last few decades, India has seen an incessant increase of tractor use as well as expansi... more Over the last few decades, India has seen an incessant increase of tractor use as well as expansion in its domestic tractor manufacturing industry, in spite of comparatively slow wage growth and a slow decline in the employment share of the agricultural sector. If the present situation is to be accounted, arguably as much as 90% of the country’s farm area may be prepared by tractors. Monomolecular nonlinear growth model methodology was applied to Punjab’s tractor density time-series data to capture the diffusion of tractor. Levenberg-Marquardt iterative method was applied with the help of SAS by using PROC NLIN statement and the obtained results show that the model is a good fit for the data under consideration. Further, Compound annual growth rate (CAGR) of tractor density was also calculated to infer about the changes in tractor density over the time (1982–2015 ) and found that CAGR was high during 80s and 90s than 2000s. Despite of low growth in last decade, Punjab is expec...

Research paper thumbnail of Forecasting long range dependent time series with exogenous variable using ARFIMAX model

The Indian Journal of Agricultural Sciences

Time series analysis and forecasting is one of the challenging issues of statistical modelling. M... more Time series analysis and forecasting is one of the challenging issues of statistical modelling. Modelling of price and forecasting is a vital matter of concern for both the farming community and policy makers, especially in agriculture. Many practical agricultural data, principally commodity price data shows the typical feature of long memory process or long range dependency. For capturing the long memory behavior of the data Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is generally used. Sometimes, in time series data besides the original series, data on some auxiliary or exogenous variables may be available or can be made available with a lower cost; like besides the market prices of commodities, market arrivals for that commodity may be available and it affects the market price of commodities. This type of exogenous variable may be incorporated in existing model to improve the model performance and forecasting accuracy, like Autoregressive Fractionally Int...

Research paper thumbnail of Screening of advanced breeding lines for high temperature tolerance using biochemical parameters in Indian mustard (Brassica juncea)

The Indian Journal of Agricultural Sciences

A set of 30 advanced breeding lines of Brassica juncea were screened for heat tolerance in terms ... more A set of 30 advanced breeding lines of Brassica juncea were screened for heat tolerance in terms of biochemical parameters in field condition at ICAR-DRMR. The selection was based on (1) early sowing (ES) (September) when average soil temperature was 41ᵒC and atmospheric temperature was around 35ºC so that heat stress coincided with seedling growth and (2) normal sown (NS) (mid October) where soil temperature was 34.2ᵒC so that seedling growth did not coincide with any stress. Various biochemical parameters like total chlorophyll, total carotenoid content, total antioxidant capacity, radical scavenging activity, lipid peroxidation and proline content were measured in leaves at flowering stage to evaluate the variability among the genotypes and comparison between ES and NS was done. Stress susceptibility index (SSI) categorized genotype NPJ-124 and DRMR-1165-40 to be highly tolerant. Correlation analysis among all the traits showed total antioxidant capacity to be significantly corre...

Research paper thumbnail of An Arima-Lstm Model for Predicting Volatile Agricultural Price Series with Random Forest Technique

Research paper thumbnail of A study on characterisation of antimicrobial resistance and antibiotic susceptibility pattern in late preterm and term neonates in a tertiary hospital, Imphal

International Journal of Contemporary Pediatrics

Background: Neonatal sepsis is defined as a clinical syndrome of bacteremia with systemic signs a... more Background: Neonatal sepsis is defined as a clinical syndrome of bacteremia with systemic signs and symptoms of infection in the first four weeks of life. It may further be divided into two main classes: early onset sepsis, which presents within the first 72 hours of birth and late onset sepsis, which usually presents after 72 hours after birth. The pattern of organisms causing neonatal sepsis has been constantly changing and the indiscriminate use of antibiotics had resulted in the emergence of multidrug resistant and virulent organisms. This study aimed to evaluate neonatal infections and the antibiotic susceptibility patterns.Methods: An institution based cross sectional study in a NICU of a tertiary care hospital. Cases enrolled were both intra and extramural who got admitted during the study period. Informed consent was obtained from the parents/guardians.Results: There were a total of 138 participants in the study. All of them tested positive for sepsis screen. Neonatal sepsis...

Research paper thumbnail of Evaluation of major anti-nutritional factors in oilseed Brassica

Research paper thumbnail of Growth modelling and forecasting of common carp and silver carp in culture ponds: A re-parametrisation approach

The available forecasting models for growth pattern in fish are based on either classical approac... more The available forecasting models for growth pattern in fish are based on either classical approach or a particular growth model. In the present study, reparamerisation methodologies were attempted for forecasting growth of fish cultured in cemented ponds of plain areas. Forecasting methodology is not readily available for any other types of ponds for uplands of India. So, other appropriate growth curves (Logistic, Gompertz and von-Bertalanffy) were considered while developing the most suitable model for forecasting fish (common carp Cyprinus carpio var communis and silver carp Hypophthalmichthys molitrix) production from cemented ponds. Gompertz-1 and Logistic-1 models gave the best fit as well as fish yield forecasting, two months ahead from various ponds

Research paper thumbnail of Long memory in conditional variance

Research paper thumbnail of BayesBEKK: Bayesian Estimation of Bivariate Volatility Model

Research paper thumbnail of Forecasting volatile time-series data through Stochastic volatility model

ICAR, 2013

In agriculture, data are usually collected over time. In the early stages of time-series analysis... more In agriculture, data are usually collected over time. In the early stages of time-series analysis, main interest was to find a model which could explain effectively the mean behaviour of data (Box et al. 2008). Subsequently, concerns about volatility or variance in the data have been raised because changes or patterns in volatility are observed in real data. As emphasized by Jaffee (2005), volatility seems to be the norm rather than exception in international markets for agricultural commodities due to structure of trade, climatic conditions, and rapidity with which producers can respond to price changes. The exports of many agricultural commodities show a great degree of fluctuations, caused by delays between production decisions and delivery to the market. Deo et al. (2008) empirically examined the implied volatility function for selected individual equity call options from Indian Stock Market. The authors also evaluated the implied volatilities of in-the-money option which were higher than implied volatility of out-of-the-money option. Bauwens et al. (2012) have given an excellent description of various aspects of volatility models and their applications. A huge amount of fruits and vegetables seeds are exported from India worldwide. The capital gained from export of seeds fluctuates due to various reasons, like variable market prices, production, time lags between production decisions

Research paper thumbnail of R package 'BayesARIMAX' : Bayesian Estimation of ARIMAX Model

Research paper thumbnail of Genetic Algorithm Based Improved ESTAR Nonlinear Models for Modelling Sunspot Numbers and Global Temperatures

Smooth Transition Autoregressive (STAR) models are employed to describe cyclical data. As estimat... more Smooth Transition Autoregressive (STAR) models are employed to describe cyclical data. As estimation of parameters of STAR using nonlinear methods was time-consuming, Genetic algorithm (GA), a powerful optimization procedure was applied for the same. Further, optimal one step and two step ahead forecasts along with their forecast error variances are derived theoretically for fitted STAR model using conditional expectations. Given the importance of the issue of global warming, the current paper aims to model the sunspot numbers and global mean temperatures. Further, appropriate tests are carried out to see if the model employed is appropriate for the datasets.

Research paper thumbnail of A Comparative Study on Time-delay Neural Network and GARCH Models for Forecasting Agricultural Commodity Price Volatility

In this paper, forecasting performance of time-delay neural network and GARCH models for predicti... more In this paper, forecasting performance of time-delay neural network and GARCH models for predicting the volatility using monthly price series of edible oils in domestic and international markets is evaluated. An attempt has also been made to investigate whether the forecasting performance of two competing models can be improved by combining their individual forecasts. For this purpose, the individual models were combined to produce improved forecasts using non-parametric approach through the use of kernel. Further, the models were evaluated on their ability to predict the correct change of direction (CCD) for future values.

Research paper thumbnail of Price volatility spillover of Indian onion markets: A comparative study

The Indian Journal of Agricultural Sciences

To investigate the interdependence between Indian onion markets in terms of price volatility, the... more To investigate the interdependence between Indian onion markets in terms of price volatility, the present study was conducted in four different vital onion markets in India, viz. Mumbai, Nashik, Delhi and Bengaluru. The long term monthly data, from March, 2003 to September, 2015 was collected from the website of agmarknet.nic.in. We have employed the VEC-MGARCH model to estimate mean and volatility spillover simultaneously among the different markets and also examined the nature of dynamic correlation using the DCC model. The presence of mean and volatility spillover was found between the markets. This type of significant interaction between the volatility of different markets is highly useful for cross market hedging and for sharing of common information by market participants. The empirical results also suggest for a very close observation on different market behavioral pattern since, “news” in one market may impact other market through the number of interdependencies. Key words: ...

Research paper thumbnail of Stochastic volatility in mean model for capturing the conditional variance in volatile time series data

The Indian Journal of Agricultural Sciences

Research paper thumbnail of Forecasting of crop yield using weather parameters - two step nonlinear regression model approach

The Indian Journal of Agricultural Sciences

Concept of the paper is firstly to remove the trend of crop yield and then to develop the forecas... more Concept of the paper is firstly to remove the trend of crop yield and then to develop the forecasting models using detrended yield. Not much work is available or development of forecast models or modelling due to their non-linear behaviour. For that, in this paper, methodology developed for forecasting using nonlinear growth models, which will help in forecasting yield, pest and disease incidences etc with high accuracy. Crop yield forecast models for wheat crop have been developed (using non-linear growth models, linear models and weather indices approach with weekly weather data) for different districts of Uttar Pradesh (UP). Weather Indices (WI) were obtained using above two approaches. Weather indices based regression models were developed using weather indices as independent variables while character under study such as crop yield was used as dependent variable for wheat crop, i.e. two step non-linear forecast model. Technique of forecasting using non-linear approach and using ...

Research paper thumbnail of Performance evaluation of yield crop forecasting models using weather index regression analysis

The Indian Journal of Agricultural Sciences

A crop forecast is a statement of the most likely magnitude of yield or production of a crop. It ... more A crop forecast is a statement of the most likely magnitude of yield or production of a crop. It is made on the basis of known facts on a given date and it assumes that the weather conditions and damages during the remainder of the growing season will be about the same as the average of previous year. The present paper deals with use of non-linear regression analysis for developing wheat yield forecast model for Allahabad district (India). A novel statistical approach attempted in this study to use nonlinear models with different weather variables and their indices and compare them to identify a suitable forecasting model. Time series yield data of 40 years (1970-2010) and weather data for the year 1970-71 to 2009-10 have been utilized. The models have been used to forecast yield in the subsequent three years 2008-09 to 2009-10 (which were not included in model development). The approach provided reliable yield forecast about two months before harvest.

Research paper thumbnail of Wheat yield forecast using detrended yield over a sub-humid climatic environment in five districts of Uttar Pradesh, India

The Indian Journal of Agricultural Sciences

A study was carried out to forecast the yield of the wheat crop for five districts of Uttar Prade... more A study was carried out to forecast the yield of the wheat crop for five districts of Uttar Pradesh namely Lucknow, Kanpur, Banda, Jhansi and Faizabad. The daily weather data on variables such as maximum temperature, rainfall, minimum temperature, and relative humidity were arranged week wise from sowing to harvesting and the relations between the weather variables and yield was worked out using statistical tools like correlation and regression. The yield has been detrended by obtaining the parameter estimates of the model and subsequently the detrended yield was used to forecast the yield of the crop using ARIMA model. The proposed method of obtaining pre-harvest forecasting of yield of crops was compared with the traditional approaches of forecasting and the proposed method was evaluated in terms of criteria's such as goodness of fit of the model. It was observed that in all the districts the proposed model performed better as compared to the traditional method both in terms o...

Research paper thumbnail of Pre harvest forecasting of crop yield using non-linear regression modelling: A concept

The Indian Journal of Agricultural Sciences

The concept of pre-harvesting of crop yield using nonlinear growth models and detrended yield for... more The concept of pre-harvesting of crop yield using nonlinear growth models and detrended yield for developing yield forecast model is rarely employed in forecasting. A novel approach attempted in this study to use nonlinear models with different weather variables and their indices and compare them to identify a suitable forecasting model. Weather indices based regression models were developed using weather indices as independent variables whiledetrended yield (residuals) was considered as dependent variable. The approach provided reliable yield forecastabout two months before harvest.

Research paper thumbnail of Forecasting crop yield through weather indices through LASSO

The Indian Journal of Agricultural Sciences

Reliable forecast of crop production before the harvest is important for advance planning, formul... more Reliable forecast of crop production before the harvest is important for advance planning, formulation and implementation policies dealing with food procurement, its distribution, pricing structure, import and export decisions, and storage and marketing of the agricultural commodities. Weather plays a very important role in crop growth and development. Therefore, model based on weather variables can provide reliable forecast. Weather variables used can be employed for crop production forecast by making appropriate models. In this study, a statistical model is used for crop yield forecast at different growth stages of wheat crop. This model uses maximum and minimum temperature, rainfall, morning and evening relative humidity during crop growing period. The forecast model was developed using generated weather indices as regressors in model. In order to select significant weather variables affecting the yield of crop least absolute shrinkage and selection operator (LASSO) as well as st...

Research paper thumbnail of Growth and diffusion dynamics of tractor in Punjab

The Indian Journal of Agricultural Sciences

Over the last few decades, India has seen an incessant increase of tractor use as well as expansi... more Over the last few decades, India has seen an incessant increase of tractor use as well as expansion in its domestic tractor manufacturing industry, in spite of comparatively slow wage growth and a slow decline in the employment share of the agricultural sector. If the present situation is to be accounted, arguably as much as 90% of the country’s farm area may be prepared by tractors. Monomolecular nonlinear growth model methodology was applied to Punjab’s tractor density time-series data to capture the diffusion of tractor. Levenberg-Marquardt iterative method was applied with the help of SAS by using PROC NLIN statement and the obtained results show that the model is a good fit for the data under consideration. Further, Compound annual growth rate (CAGR) of tractor density was also calculated to infer about the changes in tractor density over the time (1982–2015 ) and found that CAGR was high during 80s and 90s than 2000s. Despite of low growth in last decade, Punjab is expec...

Research paper thumbnail of Forecasting long range dependent time series with exogenous variable using ARFIMAX model

The Indian Journal of Agricultural Sciences

Time series analysis and forecasting is one of the challenging issues of statistical modelling. M... more Time series analysis and forecasting is one of the challenging issues of statistical modelling. Modelling of price and forecasting is a vital matter of concern for both the farming community and policy makers, especially in agriculture. Many practical agricultural data, principally commodity price data shows the typical feature of long memory process or long range dependency. For capturing the long memory behavior of the data Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is generally used. Sometimes, in time series data besides the original series, data on some auxiliary or exogenous variables may be available or can be made available with a lower cost; like besides the market prices of commodities, market arrivals for that commodity may be available and it affects the market price of commodities. This type of exogenous variable may be incorporated in existing model to improve the model performance and forecasting accuracy, like Autoregressive Fractionally Int...

Research paper thumbnail of Screening of advanced breeding lines for high temperature tolerance using biochemical parameters in Indian mustard (Brassica juncea)

The Indian Journal of Agricultural Sciences

A set of 30 advanced breeding lines of Brassica juncea were screened for heat tolerance in terms ... more A set of 30 advanced breeding lines of Brassica juncea were screened for heat tolerance in terms of biochemical parameters in field condition at ICAR-DRMR. The selection was based on (1) early sowing (ES) (September) when average soil temperature was 41ᵒC and atmospheric temperature was around 35ºC so that heat stress coincided with seedling growth and (2) normal sown (NS) (mid October) where soil temperature was 34.2ᵒC so that seedling growth did not coincide with any stress. Various biochemical parameters like total chlorophyll, total carotenoid content, total antioxidant capacity, radical scavenging activity, lipid peroxidation and proline content were measured in leaves at flowering stage to evaluate the variability among the genotypes and comparison between ES and NS was done. Stress susceptibility index (SSI) categorized genotype NPJ-124 and DRMR-1165-40 to be highly tolerant. Correlation analysis among all the traits showed total antioxidant capacity to be significantly corre...

Research paper thumbnail of An Arima-Lstm Model for Predicting Volatile Agricultural Price Series with Random Forest Technique

Research paper thumbnail of A study on characterisation of antimicrobial resistance and antibiotic susceptibility pattern in late preterm and term neonates in a tertiary hospital, Imphal

International Journal of Contemporary Pediatrics

Background: Neonatal sepsis is defined as a clinical syndrome of bacteremia with systemic signs a... more Background: Neonatal sepsis is defined as a clinical syndrome of bacteremia with systemic signs and symptoms of infection in the first four weeks of life. It may further be divided into two main classes: early onset sepsis, which presents within the first 72 hours of birth and late onset sepsis, which usually presents after 72 hours after birth. The pattern of organisms causing neonatal sepsis has been constantly changing and the indiscriminate use of antibiotics had resulted in the emergence of multidrug resistant and virulent organisms. This study aimed to evaluate neonatal infections and the antibiotic susceptibility patterns.Methods: An institution based cross sectional study in a NICU of a tertiary care hospital. Cases enrolled were both intra and extramural who got admitted during the study period. Informed consent was obtained from the parents/guardians.Results: There were a total of 138 participants in the study. All of them tested positive for sepsis screen. Neonatal sepsis...

Research paper thumbnail of Evaluation of major anti-nutritional factors in oilseed Brassica

Research paper thumbnail of Growth modelling and forecasting of common carp and silver carp in culture ponds: A re-parametrisation approach

The available forecasting models for growth pattern in fish are based on either classical approac... more The available forecasting models for growth pattern in fish are based on either classical approach or a particular growth model. In the present study, reparamerisation methodologies were attempted for forecasting growth of fish cultured in cemented ponds of plain areas. Forecasting methodology is not readily available for any other types of ponds for uplands of India. So, other appropriate growth curves (Logistic, Gompertz and von-Bertalanffy) were considered while developing the most suitable model for forecasting fish (common carp Cyprinus carpio var communis and silver carp Hypophthalmichthys molitrix) production from cemented ponds. Gompertz-1 and Logistic-1 models gave the best fit as well as fish yield forecasting, two months ahead from various ponds

Research paper thumbnail of Long memory in conditional variance

Research paper thumbnail of BayesBEKK: Bayesian Estimation of Bivariate Volatility Model

Research paper thumbnail of Forecasting volatile time-series data through Stochastic volatility model

ICAR, 2013

In agriculture, data are usually collected over time. In the early stages of time-series analysis... more In agriculture, data are usually collected over time. In the early stages of time-series analysis, main interest was to find a model which could explain effectively the mean behaviour of data (Box et al. 2008). Subsequently, concerns about volatility or variance in the data have been raised because changes or patterns in volatility are observed in real data. As emphasized by Jaffee (2005), volatility seems to be the norm rather than exception in international markets for agricultural commodities due to structure of trade, climatic conditions, and rapidity with which producers can respond to price changes. The exports of many agricultural commodities show a great degree of fluctuations, caused by delays between production decisions and delivery to the market. Deo et al. (2008) empirically examined the implied volatility function for selected individual equity call options from Indian Stock Market. The authors also evaluated the implied volatilities of in-the-money option which were higher than implied volatility of out-of-the-money option. Bauwens et al. (2012) have given an excellent description of various aspects of volatility models and their applications. A huge amount of fruits and vegetables seeds are exported from India worldwide. The capital gained from export of seeds fluctuates due to various reasons, like variable market prices, production, time lags between production decisions

Research paper thumbnail of R package 'BayesARIMAX' : Bayesian Estimation of ARIMAX Model

Research paper thumbnail of Genetic Algorithm Based Improved ESTAR Nonlinear Models for Modelling Sunspot Numbers and Global Temperatures

Smooth Transition Autoregressive (STAR) models are employed to describe cyclical data. As estimat... more Smooth Transition Autoregressive (STAR) models are employed to describe cyclical data. As estimation of parameters of STAR using nonlinear methods was time-consuming, Genetic algorithm (GA), a powerful optimization procedure was applied for the same. Further, optimal one step and two step ahead forecasts along with their forecast error variances are derived theoretically for fitted STAR model using conditional expectations. Given the importance of the issue of global warming, the current paper aims to model the sunspot numbers and global mean temperatures. Further, appropriate tests are carried out to see if the model employed is appropriate for the datasets.

Research paper thumbnail of A Comparative Study on Time-delay Neural Network and GARCH Models for Forecasting Agricultural Commodity Price Volatility

In this paper, forecasting performance of time-delay neural network and GARCH models for predicti... more In this paper, forecasting performance of time-delay neural network and GARCH models for predicting the volatility using monthly price series of edible oils in domestic and international markets is evaluated. An attempt has also been made to investigate whether the forecasting performance of two competing models can be improved by combining their individual forecasts. For this purpose, the individual models were combined to produce improved forecasts using non-parametric approach through the use of kernel. Further, the models were evaluated on their ability to predict the correct change of direction (CCD) for future values.