Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Central Bank of Nigeria (21)
- Georgia Southern University (5)
- Southern Methodist University (5)
- Purdue University (4)
- University of Kentucky (4)
-
- California Polytechnic State University, San Luis Obispo (3)
- Michigan Technological University (3)
- Claremont Colleges (2)
- Embry-Riddle Aeronautical University (2)
- Florida Institute of Technology (2)
- Louisiana Tech University (2)
- Singapore Management University (2)
- West Virginia University (2)
- Brigham Young University (1)
- California State University, San Bernardino (1)
- Clemson University (1)
- Dartmouth College (1)
- Duquesne University (1)
- East Tennessee State University (1)
- Hunan Provincial Institute of Scientific and Technology Information (1)
- Kennesaw State University (1)
- Lawrence University (1)
- Louisiana State University (1)
- Minnesota State University, Mankato (1)
- Murray State University (1)
- Rochester Institute of Technology (1)
- South Dakota State University (1)
- Southern Adventist University (1)
- The University of San Francisco (1)
- University at Albany, State University of New York (1)
- Keyword
-
- Machine learning (10)
- Machine Learning (9)
- Deep Learning (5)
- Neural Networks (4)
- Statistics (4)
-
- Artificial Intelligence (3)
- Computer vision (3)
- Nigeria (3)
- Remote sensing (3)
- Anomaly detection (2)
- COVID-19 (2)
- Clustering (2)
- Cybersecurity (2)
- Deep learning (2)
- Economic Growth (2)
- GARCH (2)
- Monetary policy (2)
- Neural Network (2)
- Neural networks (2)
- Pure sciences (2)
- Random Forest (2)
- Recurrent Neural Networks (2)
- Reinforcement Learning (2)
- Sampling (2)
- Simulation (2)
- Stock market (2)
- XGBoost (2)
- AI (1)
- ANNs (1)
- ARCH (1)
- Publication Year
- Publication
-
- CBN Journal of Applied Statistics (JAS) (21)
- College of Graduate Studies: Theses & Dissertations (5)
- SMU Data Science Review (4)
- Dissertations, Master's Theses and Master's Reports (3)
- CMC Senior Theses (2)
-
- Doctoral Dissertations (2)
- Electronic Theses and Dissertations (2)
- Graduate Theses, Dissertations, and Problem Reports (ETD) (2)
- Master's Theses (2)
- Research Collection School Of Computing and Information Systems (2)
- The Journal of Purdue Undergraduate Research (2)
- Theses and Dissertations (2)
- Theses and Dissertations--Computer Science (2)
- Theses and Dissertations--Mathematics (2)
- All Graduate Theses, Dissertations, and Other Capstone Projects (1)
- All Theses (1)
- Articles (1)
- Beyond: Undergraduate Research Journal (1)
- Campus Research Month (1)
- Computer Science Senior Theses (1)
- Computer Science and Engineering Dissertations - Archive (1)
- Creative Activity and Research Day - CARD (1)
- Department of Agricultural and Biological Systems Engineering: Faculty Publications (1)
- Doctoral Dissertations and Master's Theses (1)
- Electrical Engineering and Computer Science Undergraduate Honors Theses (1)
- Electrical and Computer Engineering ETDs (1)
- Electronic Theses & Dissertations (2024 - present) (1)
- Electronic Theses, Projects, and Dissertations (1)
- Honors Theses and Capstones (1)
- I-GUIDE Forum (1)
- Publication Type
Articles 61 - 81 of 81
Full-Text Articles in Applied Statistics
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
McKelvey School of Engineering Graduate Student Theses & Dissertations
Machine learning is a rapidly evolving field in computer science with increasingly many applications to other domains. In this thesis, I present a Bayesian machine learning approach to solving a problem in theoretical surface science: calculating the preferred active site on a catalyst surface for a given adsorbate molecule. I formulate the problem as a low-dimensional objective function. I show how the objective function can be approximated into a certain confidence interval using just one iteration of the self-consistent field (SCF) loop in density functional theory (DFT). I then use Bayesian optimization to perform a global search for the solution. …
Oriented Object Proposals, Shengfeng He, Rynson W. H. Lau
Oriented Object Proposals, Shengfeng He, Rynson W. H. Lau
Research Collection School Of Computing and Information Systems
In this paper, we propose a new approach to generate oriented object proposals (OOPs) to reduce the detection error caused by various orientations of the object. To this end, we propose to efficiently locate object regions according to pixelwise object probability, rather than measuring the objectness from a set of sampled windows. We formulate the proposal generation problem as a generative probabilistic model such that object proposals of different shapes (i.e., sizes and orientations) can be produced by locating the local maximum likelihoods. The new approach has three main advantages. First, it helps the object detector handle objects of different …
Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su
Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su
MODVIS Workshop
We propose a combinatorial approach built on Grenander’s pattern theory to generate semantic interpretations of video events of human activities. The basic units of representations, termed generators, are linked with each other using pairwise connections, termed bonds, that satisfy predefined relations. Different generators are specified for different levels, from (image) features at the bottom level to (human) actions at the highest, providing a rich representation of items in a scene. The resulting configurations of connected generators provide scene interpretations; the inference goal is to parse given video data and generate high-probability configurations. The probabilistic structures are imposed using energies that …
Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade
Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade
CBN Journal of Applied Statistics (JAS)
Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the pseudo-out-of-sample forecasting procedure over July 2011 to September 2013. According to the results the best forecasting performance is demonstrated by the model based on the all items CPI estimated using the SARIMAX model. This model is, therefore, recommended for use in short-term forecasting of headline inflation in Nigeria. The forecasting performance up to eight months ahead, of the models based on …
An Efficient Two Sample Capture-Recapture Model With High Recaptures, Danjuma Jibasen, Yusuf J. Adams
An Efficient Two Sample Capture-Recapture Model With High Recaptures, Danjuma Jibasen, Yusuf J. Adams
CBN Journal of Applied Statistics (JAS)
This paper proposed an efficient two sample capture-recapture model (Ma) with high recaptures and compared it with the existing models like the model of no factor effect (Mo), behavioral response model (Mb) and the Petersen model (Ms), using simulated data. We found that the Petersen model provides a better estimate of the population size when the observations follow a hypergeometric distribution and the population is overestimated when recapture is high. It was also found that the proposed model provides a better estimator of the population size than the existing ones when the recapture is high. This model is particularly useful …
Causal Relationship Between Stock Market Index And Exchange Rate: Evidence From Nigeria, Abdulrasheed Zubair
Causal Relationship Between Stock Market Index And Exchange Rate: Evidence From Nigeria, Abdulrasheed Zubair
CBN Journal of Applied Statistics (JAS)
This paper uses Johansen’s cointegration to test for the possibility of cointegration and Granger-causality to estimate the causal relationship between stock market index and monetary indicators (exchange rate and M2) before and during the global financial crisis for Nigeria, using monthly data for the period 2001–2011. Results suggest absence of long-run relationship before and during the crisis. The Granger-causality tests show a uni-directional causality running from M2 to ASI before the crisis while during the period of the crisis there is absence of causality between the variables. This suggests that ASI show responsiveness to M2. Thus, absence of the direct …
Investigating Chaos In The Nigerian Asset And Resource Management (Arm) Discovery Fund, Ibiyinka A. Fuwape, Samuel T. Ogunjo
Investigating Chaos In The Nigerian Asset And Resource Management (Arm) Discovery Fund, Ibiyinka A. Fuwape, Samuel T. Ogunjo
CBN Journal of Applied Statistics (JAS)
This paper investigates chaos in a Nigerian mutual fund, Asset and Resource Management Company Limited (ARM) for a period of eleven years. The existence of chaotic signals in the data was identified by the reconstruction of the phase space of the daily closing price of the fund and the delay time was quantified using mutual information function and the embedding dimension by the false nearest neighbours, where the values were identified to be 15 and 20 respectively. The presence of chaotic signals in the ARM data was further confirmed by the correlation dimension method which yielded a dimension of 2.2 …
Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete
Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete
CBN Journal of Applied Statistics (JAS)
This work considers the application of Periodogram and Fourier Series Analysis to model all-items monthly inflation rates in Nigeria from 2003 to 2011. The main objectives are to identify inflation cycles, fit a suitable model to the data and make forecasts of future values. To achieve these objectives, monthly all-items inflation rates for the period were obtained from the Central Bank of Nigeria (CBN) website. Periodogram and Fourier series methods of analysis are used to analyze the data. Based on the analysis, it was found that inflation cycle within the period was fifty one (51) months, which coincides with the …
Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya
Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya
CBN Journal of Applied Statistics (JAS)
This paper attempts to fit the best Generalized Autoregressive Conditional Heteroscedastic (GARCH) model for All Share Index (ASI) of Nigerian Stock Exchange (NSE) returns. A search is made on various GARCH variants specified on the assumptions of stationarity and asymmetry. Fractionally integrated types are also considered to capture the possibility of return series having property of long range dependency. The parameter estimations are carried out on the assumptions of normality and non-normality of GARCH innovations, with models and forecasts evaluated using information criteria and loss functions respectively. Under normality assumption, Hyperbolic GARCH (HYGARCH(1,d,1)) model is selected and Integrated GARCH (IGARCH(1,1)) …
Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim
Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim
CBN Journal of Applied Statistics (JAS)
This paper discusses the levels and trend of external reserves in Nigeria. The relevance of this lies in the fact that it could help to monitor the reserves and throw early warning signal about any economic crisis. Monthly data on Nigeria external reserves for the period January 1999 to December, 2008 derived from the 2008 CBN Statistical Bulletin was analyzed using ARIMA model. Results of the analyses show that (i) the data requires logarithmic transformation to stabilize the variance and make the distribution normal (ii) the appropriate model that best describes the pattern in the transformed data is the Autoregressive- …
A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom
A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom
CBN Journal of Applied Statistics (JAS)
A recurrent problem in manpower control is how to attain the desired structural configuration in an optimal way, since it is possible to reach a desired structural configuration using different control inputs. The major aim of this paper is to develop a Markov Decision Process for optimal control of a Multi-level Hierarchical Manpower System (MHMS) by promotion and interdepartmental transfers. This is examined under control by intervention and contraction cost Markov Decision Process.
Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts
Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts
Lawrence University Honors Projects
Artificial intelligence seeks to create intelligent agents. An agent can be anything: an autopilot, a self-driving car, a robot, a person, or even an anti-virus system. While the current state-of-the-art may not achieve intelligence (a rather dubious thing to quantify) it certainly achieves a sense of autonomy. A key aspect of an autonomous system is its ability to maintain and guarantee safety—defined as avoiding some set of undesired outcomes. The piece of software responsible for this is called a planner, which is essentially an automated problem solver. An advantage computer planners have over humans is their ability to consider and …
Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi
Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi
CBN Journal of Applied Statistics (JAS)
This study analyzed the trends and pattern of institutional credit supply to agriculture during pre- and post-financial reforms along with their determinants. It then compared the effects of reform policies on access to institutional credits in Nigerian agricultural sector before and after the reforms (1978 - 1985; and 1986 -2009). Relying mainly on time series data from CBN and NBS, it used ordinary least squares method (linear, semi-log and double log) to model the determinants of banking sector lending to the agricultural sector during the review period. The models were subjected to several econometric tests before accepting one. Chow test …
Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba
Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba
CBN Journal of Applied Statistics (JAS)
On global scale, central banks’ holdings of foreign reserves have escalated sharply in recent years. World international reserves holdings have risen significantly from US$1.2 trillion in 1995 to nearly US$10.0 trillion in June 2011. Dominant among these reserves are concentrated in the hands of few countries. Ten major holders of foreign reserves are mostly from Asia. Oil exporting countries in Africa and the Middle East are not left out in this trend. Nigeria’s foreign reserves rose from US$5.5 billion in 1999 to US$62.40 billion in July 2008, making Nigeria the twenty-fourth largest reserves holder in the world. This pace of …
Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan
Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan
CBN Journal of Applied Statistics (JAS)
This study investigates the effect of exchange rate movements on real output growth in Nigeria. Based on quarterly series for the period 1986 to 2010, the paper examines the possible direct and indirect relationship between exchange rates and GDP growth. The relationship is derived in two ways using a simultaneous equations model within a fully specified (but small) macroeconomic model. A Generalised Method of Moments (GMM) technique was explored. The estimation results suggest that there is no evidence of a strong direct relationship between changes in exchange rate and output growth. Rather, Nigeria’s economic growth has been directly affected by …
Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda
Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda
CBN Journal of Applied Statistics (JAS)
The adoption of the International Monetary Fund (IMF) Structural Adjustment Programme (SAP) in 1986 resulted in the transition from fixed exchange rate regime to floating exchange rate regime in Nigeria. Ever since, the exchange rate of naira vis-à-vis the U.S dollar has attained varying rates all through different time horizons. On this basis, this study examines the consistency, persistency, and severity (degree) of volatility in exchange rate of Nigerian currency (naira) vis-a-vis the United State dollar using monthly time series data from 1986 to 2008. The standard Purchasing Power Parity (PPP) model was used to analyze the long-run consistency of …
Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari
Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari
CBN Journal of Applied Statistics (JAS)
This research uses a cointegration VAR model to study the contemporaneous long-run dynamics of the impact of Foreign Private Investment (FPI), Interest Rate (INR) and Inflation rate (IFR) on Growth Domestic Products (GDP) in Nigeria for the period January 1970 to December 2009. The Unit Root Test suggests that all the variables are integrated of order 1. The VAR model was appropriately identified using AIC information criteria and the VECM model has exactly one cointegration relation. The study further investigates the causal relationship using the Granger causality analysis of VECM which indicates a uni-directional causality relationship between GDP and FDI …
Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola
Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola
CBN Journal of Applied Statistics (JAS)
The paper examines the relationship between banking sector credit and economic growth in Nigeria over the period 1970-2008. The causal links between the pairs of variables of interest were established using Granger causality test while a Two-Stage Least Squares (TSLS) estimation technique was used for the regression models. The results of Granger causality test show evidence of unidirectional causal relationship from GDP to private sector credit (PSC) and from industrial production index (IND) to GDP. Estimated regression models indicate that private sector credit impacts positively on economic growth over the period of coverage in this study. However, lending (interest) rate …
Early Stopping Of A Neural Network Via The Receiver Operating Curve., Daoping Yu
Early Stopping Of A Neural Network Via The Receiver Operating Curve., Daoping Yu
Electronic Theses and Dissertations
This thesis presents the area under the ROC (Receiver Operating Characteristics) curve, or abbreviated AUC, as an alternate measure for evaluating the predictive performance of ANNs (Artificial Neural Networks) classifiers. Conventionally, neural networks are trained to have total error converge to zero which may give rise to over-fitting problems. To ensure that they do not over fit the training data and then fail to generalize well in new data, it appears effective to stop training as early as possible once getting AUC sufficiently large via integrating ROC/AUC analysis into the training process. In order to reduce learning costs involving the …
Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara
Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara
Doctoral Dissertations
In this study, I investigate and conduct an experiment on two-stage clustering procedures, hybrid models in simulated environments where conditions such as collinearity problems and cluster structures are controlled, and in real-life problems where conditions are not controlled. The first hybrid model (NK) is an integration between a neural network (NN) and the k-means algorithm (KM) where NN screens seeds and passes them to KM. The second hybrid (GK) uses a genetic algorithm (GA) instead of the neural network. Both NN and GA used in this study are in their simplest-possible forms.
In the simulated data sets, I investigate two …
Fuzzy Product -Limit Estimators: Soft Computing In The Presence Of Very Small And Highly Censored Data Sets, Kian Lawrence Pokorny
Fuzzy Product -Limit Estimators: Soft Computing In The Presence Of Very Small And Highly Censored Data Sets, Kian Lawrence Pokorny
Doctoral Dissertations
When very few data are available and a high proportion of the data is censored, accurate estimates of reliability are problematic. Standard statistical methods require a more complete data set, and with any fewer data, expert knowledge or heuristic methods are required. In the current research a computational system is developed that obtains a survival curve, point estimate, and confidence interval about the point estimate.
The system uses numerical methods to define fuzzy membership functions about each data point that quantify uncertainty due to censoring. The “fuzzy” data are then used to estimate a survival curve, and the mean survival …