Annals of Data Science

Annals of Data Science (AODS) is an academic journal focusing on Big Data analytics and applications. It not only promotes how to use interdisciplinary ...

List of Papers (Total 139)

Action for Action: Mad COVID-19, Falling Markets and Rising Volatility of SAARC Region

The Southern Region has reported a large number of contagious pandemic outbreaks. These epidemics brought threats to human health and resulted in serious economic losses. The COVID-19 is a global virus and has weakened the global financial markets with significant effect on stock returns and market volatilities. The study obtained a dataset about the financial market structure of...

Student-Performulator: Predicting Students’ Academic Performance at Secondary and Intermediate Level Using Machine Learning

Forecasting academic performance of student has been a substantial research inquest in the Educational Data-Mining that utilizes Machine-learning (ML) procedures to probe the data of educational setups. Quantifying student academic performance is challenging because academic performance of students hinges on several factors. The in hand research work focuses on students’ grade...

Zero-Inflated Models for Count Data: An Application to Number of Antenatal Care Service Visits

The risk of maternal death in developing countries is projected to be one in 61, while for developed countries it is estimated to be one in 2800. Antenatal care is a protective obstetric health care system aimed at improving the outcome of the pregnant fetus by routine pregnancy monitoring. One of the most important functions of antenatal care is to offer health information and...

Modeling of COVID-19 Cases in Pakistan Using Lifetime Probability Distributions

The Coronavirus Disease (COVID-19) is a respiratory disease that caused a large number of deaths all over the world since its outbreak. The World Health Organization (WHO) has declared the outbreak a global pandemic. The understanding of the random process related to the behavior infection of COVID-19 is an important health and economic problem. In the proposed study, we analyze...

The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data

This paper aims at defining an optimal statistical model for the COVID-19 distribution in the United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the odd Weibull family introduces a new lifetime distribution with a three-parameter to formulate the odd Weibull inverted Topp–Leone (OWITL) distribution. As a simple linear representation, hazard rate...

Outbreak Prediction of COVID-19 for Dense and Populated Countries Using Machine Learning

The Coronavirus Disease-2019 (COVID-19) pandemic persists to have a mortifying impact on the health and well-being of the global population. A continued rise in the number of patients testing positive for COVID-19 has created a lot of stress on governing bodies across the globe and they are finding it difficult to tackle the situation. We have developed an outbreak prediction...

Construction of Confidence Interval for a Univariate Stock Price Signal Predicted Through Long Short Term Memory Network

In this paper, we show an innovative way to construct bootstrap confidence interval of a signal estimated based on a univariate LSTM model. We take three different types of bootstrap methods for dependent set up. We prescribe some useful suggestions to select the optimal block length while performing the bootstrapping of the sample. We also propose a benchmark to compare the...

Comparing Artificial Neural Network Architectures for Brazilian Stock Market Prediction

Prediction of financial time series is a great challenge for statistical models. In general, the stock market times series present high volatility due to its sensitivity to economic and political factors. Furthermore, recently, the covid-19 pandemic has caused a drastic change in the stock exchange times series. In this challenging context, several computational techniques have...

Modeling Determinants of Low Birth Weight for Under Five-Children in Ethiopia

Low birth weight (LBW) is a major determinant of morbidity, mortality and disability in infancy and childhood and has a long-term impact on health outcomes in adult life. This study was aimed to model LBW using marginal and generalized linear mixed models as well as identify the potential risk factors of LBW in Ethiopia. Data was taken from the 2011 Ethiopian demographic and...

Correction to: An Application of Time Truncated Single Acceptance Sampling Inspection Plan Based on Generalized Half‑Normal Distribution

In the original publication of the article, under the real life application section, commas in the observation of real examples are misplaced and the observations are changed.

Monitoring Novel Corona Virus (COVID-19) Infections in India by Cluster Analysis

It is a great challenge of identification as well as formation of groups of infectious disease data set. Data mining, a process of uncovering silent characteristics of big data is one of such techniques which have nowadays become more popular for treating massive volume of infectious disease data set. In the current study, we apply cluster analysis, one of the data mining...

Modeling of Longitudinal Factors Under-Age Five Children Body Mass Index at Bahir Dar Districts: First Order Transition Model

The body mass index (BMI) is calculated as weight in kilograms divided by square height in meters (\( \frac{\text{kg}}{{{\text{m}}^{2} }} \)). Its formula was developed by Belgium Statistician Adolphe Quetelet, and was known as the Quetelet Index (Adolphe Quetelet in BMI formula was developed. Belgium Statistician, 1796–1874. http://www.cdc.gov/healthyweight/assessing/bmi...

Odd Hyperbolic Cosine Exponential-Exponential (OHC-EE) Distribution

In the present paper, we introduce a new lifetime distribution based on the general odd hyperbolic cosine-FG model. Some important properties of proposed model including survival function, quantile function, hazard function, order statistic are obtained. In addition estimating unknown parameters of this model will be examined from the perspective of classic and Bayesian...

Statistical Modeling of Women Employment Status at Harari Region Urban Districts: Bayesian Approach

Women have always faced a number of disadvantageous gaps in the labour market; the status of women at the labour markets throughout the world has not substantially narrowed gender gaps in the workplace. Many women in developing countries are domestic workers or informal factory workers, while others are unpaid workers in family enterprises and family farms. Agriculture is the...

On Regularisation Methods for Analysis of High Dimensional Data

High dimensional data are rapidly growing in many domains due to the development of technological advances which helps collect data with a large number of variables to better understand a given phenomenon of interest. Particular examples appear in genomics, fMRI data analysis, large-scale healthcare analytics, text/image analysis and astronomy. In the last two decades...

A Dynamic Panel Gravity Model Application on the Determinant Factors of Ethiopia’s Coffee Export Performance

Ethiopia’s coffee export earning percentage share in the total export has been rapidly waning over the last decades while it is the first commodity in currency grossing of the country. Since, this study analyses the determinant factors of Ethiopia’s coffee exports (ECE) performance, in the dimension of export sales, via a more realistic model application, dynamic panel gravity...

Forecasting the Volatility of Ethiopian Birr/Euro Exchange Rate Using Garch-Type Models

This paper provides a robust analysis of volatility forecasting of Euro-ETB exchange rate using weekly data spanning the period January 3, 2000–December 2, 2015. The forecasting performance of various GARCH-type models is investigated based on forecasting performance criteria such as MSE and MAE based tests, and alternative measures of realized volatility. To our knowledge, this...

Joint Modeling of Longitudinal CD4 Count and Time-to-Death of HIV/TB Co-infected Patients: A Case of Jimma University Specialized Hospital

Tuberculosis (TB) and HIV have been closely linked since the emergence of AIDS; TB enhances HIV replication by accelerating the natural evolution of HIV infection which is the leading cause of sickness and death of peoples living with HIV/AIDS. To improve their life the co-infected patients are started to take antiretroviral treatment as patient started to take ART it is common...

Assessing Survival Time of Women with Cervical Cancer Using Various Parametric Frailty Models: A Case Study at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia

Cervical cancer is one of the leading causes of death in the world and represents a tremendous burden on patients, families and societies. It is estimated that over one million women worldwide currently have cervical cancer; most of them have not been diagnosed or have no access to treatment that could cure them or prolong their lives. The goal of this study is to investigate...

Analysis of Prevalence of Malaria and Anemia Using Bivariate Probit Model

Malaria and anemia are public health problems that have an impact on social and economic development. Malaria causes 70,000 deaths each year and accounts for 17% of outpatient visits to health institutions. It is one of the causes of anemia. Therefore, knowing the relation between malaria and anemia could have a great contribution to the development of prevention strategies. This...

Modelling Under-Five Mortality among Hospitalized Pneumonia Patients in Hawassa City, Ethiopia: A Cross-Classified Multilevel Analysis

Community acquired pneumonia refers to pneumonia acquired outside of hospitals or extended health facilities and it is a leading infectious disease. This study aims to model mortality of hospitalized under-5 year child pneumonia patients and investigate potential risk factors associated with child mortality due to pneumonia. The study was a retrospective study on 305 sampled...