Analysis of crime data using principal component analysis: A case study of Katsina State

This paper analyses Katsina State crime data which consists of the averages of eight major crimes reported to the police for the period 2006 - 2008. The crimes consist of robbery, auto theft, house and store breakings, theft/stealing, grievous hurt and wounding, murder, rape, and assault. Correlation analysis and principal component analysis (PCA) were employed to explain the correlation between the crimes and to determine the distribution of the crimes over the local government areas of the state. The result has shown a significant correlation between robbery, theft and vehicle theft. While MSW local government area has the lowest crime rate, KTN local government area has the overall crime rate in the state. Robbery is more prevalent in DMS local government area, rape in JBA local government area, and grievous hurt and wounding in DDM local government area. The PCA has suggested retaining four components that explain about 78.94 percent of the total variability of the data set

Forecasting performance of mixed data sampling (MIDAS) regressions, autoregressive distributed lag (ADL) model and hybrid of GARCH-MIDAS model: a comparative study

This paper considers the Comparison of forecasting performance between Mixed Data sampling (MIDAS) Regressions model, Autoregressive distributed lag (ARDL) Model and hybrid of GARCH-MIDAS. The data employed for this study was secondary type in nature for all the variables and it is obtained from the publications of Central Bank of Nigerian bulletin, National Bureau of Statistics and World Bank Statistics Database dated, January, 2005 to Dec, 2019. The result of unit root test shows that all variables are stationary at level and after first differences at 5% level of significant. From the results we found that F-statistics 1.895554 is inside the regions defined as the lower and upper bound (3.62 and 4.16) at 5% level of significant, this implies that there’s no long-run relationship between dependent variable (NSE) and independent Variable (CC). using forecasting evaluations with shows that that GARCH-MIDAS has a least value of RMSE and MAPE than ARDL and MIDAS model (1823.531 and 3.976542) is least than for MIDAS and Ardl models (2372.846, 4.765421 and 2134.732, 5.952348). Finally, we can conclude that GARCH- MIDAS model outperform MIDAS and ARDL models of Nigeria Stock Exchange

Variable Selection with Convex and Non-Convex Penalized Likelihood Models Using Rainfall Data

Accurate estimate of rainfall is very important for effective use of water resources and optimal planning of water structure in a day-to-day activity of life. Variable selection is an important aspect in penalization for the estimation of accurate outcome. Traditional variable selection such as stepwise and subset selections are usually used which can be computationally expensive and ignore stochastic errors in the variable selection process. Penalized likelihood methods are applied to select the important variables which can be used for accurate predictions. In this study, penalized likelihood approach is applied to select variables and estimate coefficients simultaneously. Some of penalized penalty functions were used to produce sparse solutions. From the results obtained the penalty functions produce the important variables that influence the total rainfall. Lasso model produces Four (4) important variables, Elastic net produces Two (2) important variables while SCAD produces only One (1) variable as important. This indicates that Lasso model is more complex than SCAD model. The results also show that SCAD penalty function out performed Ridge, Lasso and Elastic net. Based on the RMSE criteria, Ridge regression performed less compared to the other models

On Exponentiated Skewed Student t Error Distribution on Some Heteroscedastic Models: Evidence of Nigeria Stock Exchange

In this paper, a new error innovation distribution was proposed in estimating some heteroscedasticity models. A new error innovation distribution was proposed called Exponentiated skewed student t distribution (ESSTD) and compared with the existing error distributions with an empirical dataset using daily returns on Nigeria Stock Exchange (NSE) index return from 30/08/2007 to 30/08/2017.The data shows stationarity at level without difference data and the ADF statistic shows evidence of stationarity, there is presence of ARCH effect. The estimate of the GARCH models and its extension shows a significant probability at 1%, 5% and 10% confident intervals forthe new error distribution and the existing distributions. The AIC and RMSE shows that the new error distributions outperformed in terms of fitness and forecasting evaluation with the smallest AIC and RMSE values respectively

Effects of NPK and Cow Dung on the Performance of Rice (Oryza sativa) in the Sudan Savanna Agro-ecological Zone of Nigeria

This study evaluated the effect of Nitrogen, Phosphorus and Potassium (NPK 20-10-10) and cow dung on the performance of rice at two locations (Sokoto and Talata Mafara) in the Sudan savanna zone of Nigeria, during the 2012/2013 dry season. The treatments consisted of nine different combinations of cow dung and NPK fertilizer with an absolute control, using rice (FARO 44) as a test crop. The treatments were laid out in a Randomize Complete Block Design (RCBD) and replicated three times. The combined application of cow dung and NPK fertilizer significantly (p < 0.05) increased most of the results obtained with regards to locations compared to the control plots. The growth and yield parameters of rice considered were significantly (p <0.05) affected by the treatments except one thousand grain weight. Application of 8 t ha-1 of cow dung in combination with 400 kg ha-1 NPK 20:10:10 gave the highest grain yield (5.77 t ha-1) at Sokoto, while application of 12 t ha-1 of cow dung in combination with 300 kg ha-1 NPK 20:10:10 gave the highest grain yield (6.50 t ha-1) at Talata Mafara. In conclusion, it is recommended that application of 12 t ha-1 of cow dung in combination with 300 kg ha-1 NPK 20:10:10 resulted in the best soil nutrient enrichment and yield of rice in Sokoto and Talata Mafara. The result showed that judicious application of cow dung with NPK fertilizers could be a useful practice for better performance of Rice in the study areas compared to the control plots which significantly recorded the least.&nbsp