Empirical bayesian binary classification forests using bootstrap prior

In this paper, we present a new method called Empirical Bayesian Random Forest (EBRF) for binary classification problem. The prior ingredient for the method was obtained using the bootstrap prior technique. EBRF addresses explicitly low accuracy problem in Random Forest (RF) classifier when the number of relevant input variables is relatively lower compared to the total number of input variables. The improvement was achieved by replacing the arbitrary subsample variable size with empirical Bayesian estimate. An illustration of the proposed, and existing methods was performed using five high-dimensional microarray datasets that emanated from colon, breast, lymphoma and Central Nervous System (CNS) cancer tumours. Results from the data analysis revealed that EBRF provides reasonably higher accuracy, sensitivity, specificity and Area Under Receiver Operating Characteristics Curve (AUC) than RF in most of the datasets used

Modeling Short Run Relationship between Naira-USD Exchange Rate and Crude Oil Price in Nigeria

The vector auto-regressive (VAR) model is one of the most successful, flexible, and easy to use models for the analysis of multivariate time series. It is a natural extension of the univariate auto-regressive model to a dynamic multivariate time series.The VAR model has proven to be especially useful for describing the dynamic behavior of economic and financial time series and for forecasting. It often provides superior forecasts to those from univariate time series models. The data used are monthlyobservations from January 2006 to October 2016 of Nigeria Crude Oil price and Naira to the dollar exchange rate. The VAR model was employed for modelling the data. The unit root test reveals that all the series are non-stationary at the level and stationary at first difference. The co-integration relations among the series indices were identified by applying Johansen’s cointegration test. The result of Johansen’s test indicates no existence of co-integration relation between the variables. The final result shows that a vector autoregressive (VAR) model of lag three with no co-integration equations best fits the data

A Fractional Cointegration Panel Model With Fixed Effect

Several authors have studied fractional cointegration in time series data, but little or no consideration has been extended to panel data settings. However, recent economics and financial panel datasets such as portfolio returns across firms, price indices and exchange rates across countries often exhibit long-memory properties. Therefore, this thesis aims to develop a fractional cointegrated panel model with a fixed effect assumption. The first objective was to compare the finite sample behaviour of existing fractional cointegration time-series test procedures in panel data settings. This comparison is performed to determine the best tests that can be adapted to fractional cointegration in panel data settings. Specifically, simulation studies and real-life data analysis were performed to study the changes in the empirical type I error rate and power of six semiparametric fractional cointegration tests in panel settings. The analysis findings revealed that the residual-based tests are useful for adaptation in a panel setting. Secondly, the best two residual-based time series fractional cointegration tests observed were implemented in panel settings using Monte-Carlo simulation experiments. The results of the experiments showed that one of the tests is valid for fractional cointegration order of less than 0.5, the other is generalized and accepts any fractional cointegration order within the range [0, 1] at varying sample sizes. Finally, a fractional cointegrated panel approach was developed for testing the absolute Purchasing Power Parity (PPP) model among 16 West African countries using data that spans 49 years (1971-2019)

Testing absolute purchasing power parity in West Africa using fractional cointegration panel approach

One of the most effective ideas for comparing the values of two or more currencies is the purchasing power parity hypothesis (PPP). Most earlier works on PPP focused on using the standard cointegration approach by assuming a unit root for the observed series. This assumption is not always valid, especially in series with short-term dynamics. Thus, in this paper, we developed the fractional cointegrated panel approach for testing the absolute Purchasing Power Parity (PPP) model. The empirical illustration was achieved using the exchange rates and price ratios for the 16 West African countries for 52 years (1970 - 2021). The results from the fractional cointegration test confirm the presence of relative PPP for the panel of countries in the long run, while the estimation of long-run intercepts and cointegration vector confirms the absence of the absolute PPP for the panel of countries

An Exploratory Analysis of Human Immunodeficiency Virus (HIV) Prevalence in Nigeria

This paper involved conducting a statistical analysis on the number of individuals living with HIV/AIDS. The University of Ilorin Teaching Hospital (UITH) was chosen as the case study for the years 2014 to 2019, with factors such as year, sex, and age group taken into account. During this six-year period, a total of 2604 cases were recorded at UITH. Among both sexes, females had the highest number of people living with HIV/AIDS. Additionally, the age group of 31-45 had the highest number of individuals affected by the disease. In terms of the specific year, 2016 had the highest number of people living with the disease, totalling 460 cases. A chi-square test of independence was conducted to examine the relationship between the factors, using a significance level of 0.05. The results indicated that all the considered factors were not independent of each other, meaning they were related