Subjects -> MATHEMATICS (Total: 1013 journals)
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    - PROBABILITIES AND MATH STATISTICS (113 journals)

PROBABILITIES AND MATH STATISTICS (113 journals)                     

Showing 1 - 98 of 98 Journals sorted alphabetically
Advances in Statistics     Open Access   (Followers: 9)
Afrika Statistika     Open Access   (Followers: 1)
American Journal of Applied Mathematics and Statistics     Open Access   (Followers: 11)
American Journal of Mathematics and Statistics     Open Access   (Followers: 9)
Annals of Data Science     Hybrid Journal   (Followers: 14)
Annual Review of Statistics and Its Application     Full-text available via subscription   (Followers: 7)
Applied Medical Informatics     Open Access   (Followers: 11)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
Asian Journal of Probability and Statistics     Open Access  
Austrian Journal of Statistics     Open Access   (Followers: 4)
Biostatistics & Epidemiology     Hybrid Journal   (Followers: 4)
Cadernos do IME : Série Estatística     Open Access  
Calcutta Statistical Association Bulletin     Hybrid Journal  
Communications in Mathematics and Statistics     Hybrid Journal   (Followers: 4)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics: Case Studies, Data Analysis and Applications     Hybrid Journal  
Comunicaciones en Estadística     Open Access  
Econometrics and Statistics     Hybrid Journal   (Followers: 1)
Forecasting     Open Access   (Followers: 1)
Foundations and Trends® in Optimization     Full-text available via subscription   (Followers: 3)
Frontiers in Applied Mathematics and Statistics     Open Access   (Followers: 1)
Game Theory     Open Access   (Followers: 2)
Geoinformatics & Geostatistics     Hybrid Journal   (Followers: 14)
Geomatics, Natural Hazards and Risk     Open Access   (Followers: 13)
Indonesian Journal of Applied Statistics     Open Access  
International Game Theory Review     Hybrid Journal   (Followers: 1)
International Journal of Advanced Statistics and IT&C for Economics and Life Sciences     Open Access  
International Journal of Advanced Statistics and Probability     Open Access   (Followers: 7)
International Journal of Algebra and Statistics     Open Access   (Followers: 3)
International Journal of Applied Mathematics and Statistics     Full-text available via subscription   (Followers: 3)
International Journal of Ecological Economics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Energy and Statistics     Hybrid Journal   (Followers: 3)
International Journal of Game Theory     Hybrid Journal   (Followers: 3)
International Journal of Mathematics and Statistics     Full-text available via subscription   (Followers: 2)
International Journal of Multivariate Data Analysis     Hybrid Journal  
International Journal of Probability and Statistics     Open Access   (Followers: 4)
International Journal of Statistics & Economics     Full-text available via subscription   (Followers: 6)
International Journal of Statistics and Applications     Open Access   (Followers: 2)
International Journal of Statistics and Probability     Open Access   (Followers: 3)
International Journal of Statistics in Medical Research     Hybrid Journal   (Followers: 5)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Iraqi Journal of Statistical Sciences     Open Access  
Japanese Journal of Statistics and Data Science     Hybrid Journal  
Journal of Biometrics & Biostatistics     Open Access   (Followers: 4)
Journal of Cost Analysis and Parametrics     Hybrid Journal   (Followers: 5)
Journal of Environmental Statistics     Open Access   (Followers: 4)
Journal of Game Theory     Open Access   (Followers: 1)
Journal of Mathematical Economics and Finance     Full-text available via subscription  
Journal of Mathematics and Statistics Studies     Open Access  
Journal of Modern Applied Statistical Methods     Open Access   (Followers: 1)
Journal of Official Statistics     Open Access   (Followers: 2)
Journal of Quantitative Economics     Hybrid Journal  
Journal of Social and Economic Statistics     Open Access  
Journal of Statistical Theory and Practice     Hybrid Journal   (Followers: 2)
Journal of Statistics and Data Science Education     Open Access   (Followers: 2)
Journal of Survey Statistics and Methodology     Hybrid Journal   (Followers: 4)
Journal of the Indian Society for Probability and Statistics     Full-text available via subscription  
Jurnal Biometrika dan Kependudukan     Open Access  
Jurnal Ekonomi Kuantitatif Terapan     Open Access  
Jurnal Sains Matematika dan Statistika     Open Access  
Lietuvos Statistikos Darbai     Open Access  
Mathematics and Statistics     Open Access   (Followers: 2)
Methods, Data, Analyses     Open Access   (Followers: 1)
METRON     Hybrid Journal   (Followers: 1)
Nepalese Journal of Statistics     Open Access  
North American Actuarial Journal     Hybrid Journal   (Followers: 1)
Open Journal of Statistics     Open Access   (Followers: 3)
Open Mathematics, Statistics and Probability Journal     Open Access  
Pakistan Journal of Statistics and Operation Research     Open Access   (Followers: 1)
Physica A: Statistical Mechanics and its Applications     Hybrid Journal   (Followers: 6)
Probability, Uncertainty and Quantitative Risk     Open Access   (Followers: 2)
Ratio Mathematica     Open Access  
Research & Reviews : Journal of Statistics     Open Access   (Followers: 3)
Revista Brasileira de Biometria     Open Access  
Revista Colombiana de Estadística     Open Access  
RMS : Research in Mathematics & Statistics     Open Access  
Romanian Statistical Review     Open Access  
Sankhya B - Applied and Interdisciplinary Statistics     Hybrid Journal  
SIAM Journal on Mathematics of Data Science     Hybrid Journal   (Followers: 1)
SIAM/ASA Journal on Uncertainty Quantification     Hybrid Journal   (Followers: 2)
Spatial Statistics     Hybrid Journal   (Followers: 2)
Sri Lankan Journal of Applied Statistics     Open Access  
Stat     Hybrid Journal   (Followers: 1)
Stata Journal     Full-text available via subscription   (Followers: 8)
Statistica     Open Access   (Followers: 6)
Statistical Analysis and Data Mining     Hybrid Journal   (Followers: 23)
Statistical Theory and Related Fields     Hybrid Journal  
Statistics and Public Policy     Open Access   (Followers: 4)
Statistics in Transition New Series : An International Journal of the Polish Statistical Association     Open Access  
Statistics Research Letters     Open Access   (Followers: 1)
Statistics, Optimization & Information Computing     Open Access   (Followers: 3)
Stats     Open Access  
Synthesis Lectures on Mathematics and Statistics     Full-text available via subscription   (Followers: 1)
Theory of Probability and its Applications     Hybrid Journal   (Followers: 2)
Theory of Probability and Mathematical Statistics     Full-text available via subscription   (Followers: 2)
Turkish Journal of Forecasting     Open Access   (Followers: 1)
VARIANSI : Journal of Statistics and Its application on Teaching and Research     Open Access  
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal  

           

Similar Journals
Journal Cover
International Journal of Statistics and Applications
Number of Followers: 2  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2168-5193 - ISSN (Online) 2168-5215
Published by SAP Homepage  [105 journals]
  • The Impact of Microfinance on Poverty Reduction at the Macro Level in
           Bangladesh Comparing with That of the Traditional Banking Sector

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 3Anas AbuThis paper conducts a comparative study between Microfinance Institutions (MFIs) and the wider banking sector in Bangladesh investigating their macroeconomic impact on poverty in the long run. Microfinance has received much international acclaim in recent decades, but it is debatable whether it has helped individuals break the poverty trap. Stiglitz’s theory on ‘Peer Monitoring and Credit Markets’ suggests the poor should have greater opportunities to escape poverty through loans with little/no collateral and low-interest rates. However, during the years 1983-2016, microfinance appears to have no significant impact on poverty in Bangladesh. First, a Three-Stage Least Squares Regression assesses the relationship between microfinance credit, banking credit, the poverty gap and GDP growth. Here, microfinance has a positive impact on GDP growth but no impact on poverty, possibly because of high-interest rates in practice or a saturated micro-business market. Conversely, the banking sector reduces poverty whilst not impacting economic growth suggesting the poor have been supported through other channels for financial development, including increased access to bank branches. A Vector Autoregression Granger-Causality test has been conducted to observe causality between the financial credit variables and the poverty gap. Results show the poverty gap Granger-causes both banking credit and microfinance credit, suggesting poverty leads individuals to take loans. But this is only expected for microfinance, not the wider banking sector, which raises concerns over whether MFIs are reaching the right individuals. Overall, this study questions the effectiveness of microfinance in reducing poverty, but it is important to acknowledge that this study has been limited by a lack of data from MFIs, and further research is needed with more data.
       
  • Non-Parametric Estimator for a Finite Population Total Based on
           Saddlepoint Approximation

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 3Jacob Oketch Okungu, George Otieno Orwa, Romanus Odhiambo OtienoIn sample surveys, the main objective is to make inference about the entire population parameters using the sample statistics. In this study, a nonparametric estimator of finite population total is proposed and its coverage probabilities studied using Saddlepoint approximation. Three asymptotic properties; unbiasedness, efficiency and the confidence interval of the proposed estimator are studied. The study focusses more on length of confidence interval and coverage probabilities at the same time, the amount of bias and MSE are also studied. Simulated data using three data variables; linear, quadratic and exponential are generated to study the asymptotic properties of the proposed estimator. Based on the empirical study with simulations in R, the proposed estimator gave a comparatively smaller amount of bias and MSE compared to the nonparametric Nadaraya – Watson (Dorfman’s) estimator, the design-based Horvitz-Thompson estimator and the model-based ratio estimator. Further, the proposed estimator is tighter compared to the other three considered in this study with a higher coverage probability.
       
  • Selecting the Method to Overcome Partial and Full Multicollinearity in
           Binary Logistic Model

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 3N. Herawati, K. Nisa, NusyirwanThe aim of our study is to select the best method for overcoming partial and full multicollinearity in binary logistic model for different sample sizes. Logistic ridge regression (LRR), least absolute shrinkage and selection operator (LASSO) and principal component logistic regression (PCLR) compared to maximum likelihood estimator (MLE) using simulation data with different level of multicollinearity and different sample sizes (n=20, 50, 100, 200). The best method is chosen based on mean square error (MSE) values and the best model is characterized by AIC value. The results show that LRR, LASSO and PCLR surpass MLE in overcoming partial and full multicollinearity in binary logistic model. PCLR exceeds LRR and LASSO when full multicollinearity occurs in binary logistic model but LASSO and LRR are better used when partial multicollinearity exists in the model.
       
  • Another Two-Parameter Poisson-Sujatha Distribution

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 2Rama Shanker, Kamlesh Kumar Shukla, Tekie Asehun LeonidaIn this paper another two-parameter Poisson-Sujatha distribution by compounding Poisson distribution with another two-parameter Sujatha distribution which includes geometric distribution and Poisson-Sujatha distribution as particular cases, has been proposed. Its moments based statistical constants including coefficient of variation, skewness, kurtosis and index of dispersion have been obtained. Maximum likelihood estimation has been explained for estimating its parameters. Goodness of fit of the proposed distribution has been explained with five over-dispersed count datasets from various fields of knowledge and fit has been compared with Poisson-Lindley distribution, Poisson-Sujatha distribution, a generalization of Poisson-Sujatha distribution and two-parameter Poisson-Sujatha distribution.
       
  • Statistical Analysis on the Impact of Macroeconomic Variables on Stock
           Market Prices in Nigeria

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 2Azeez M. B., Olanrewaju S. O.This study empirically examined the impact of macroeconomic variables (exchange rate, gross domestic product, inflation and interest rate) on stock market prices in Nigeria using quarterly time series data covering the period 1989; 1 to 2018; 3. The econometric technique employed in the research is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. The econometric analysis began with pre-diagnostic test which is a pre-condition for estimating GARCH model (testing for clustering volatility and ARCH effect in the residual). Properties of the time series variables were examined and tested for stationarity using the Augmented Dickey-Fuller (ADF) unit root test. The test revealed that all the variables; all share index, exchange rate, gross domestic product, inflation and interest rate were stationary at either level I(0) or at first difference I(I). The conditional variance equation of the GARCH model revealed that GDP has positive effect on stock prices while other macroeconomic variables have negative effect on stock return volatility. The study found that stock prices is more responsive to their lag values than the variables of exchange rates, gross domestic product, inflation and Interest rate; and therefore, the study recommends the following: That Government should always embark on policies that will lead to substantial growth in the real gross domestic product; ensure that a decrease in interest rate is also accompanied by an increase in investment. Thus, interest rate should be guided by the relevant authority through a preferred range for investing firms; and finally ensure a relatively stable exchange rate and keep Inflationary trend at a single digit.
       
  • Comparison of Forecasting Models Using Nigeria Monthly Treasury Bill Rates
           Data

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 2Igbasan S. S., Olanrewaju S. O.This study compares the forecasting models of Nigeria monthly Treasury Bill Data. The analysis is based on using monthly issues bill data from January 2011 to December 2018. Treasury bill rate of two short term Treasury bills (91 day and 182 day) from the year 2011 to 2018. The data were stationary at first difference but not normally distributed. ARMA, ARIMA and SARIMA models were computed and diagnosed. From the results of parameter estimation of the models, ARMA (2, 1) model was the best model among the other ARMA models computed using information criteria, (AIC). Diagnostic test was run on the ARMA (2, 1) model where the results showed that the model was adequate and normally distributed using Box-Ljung test and Q–Q plot respectively. Furthermore, ARIMA of first and second differences were estimated and ARIMA (2, 1, 1) was the best model from the result of the AIC and diagnostic test that were run and the model was found to be adequate and normally distributed from Box- Ljung and Q-Q plot respectively than ARIMA (2, 2, 1). From the results obtained in the ARMA and ARIMA model, ARIMA (2, 1, 1) x SARIMA (2, 1, 1)12 was now estimated and found to be adequate from the result of the Box-Ljung and Q-Q plot respectively. Post forecasting estimation and performance evolution was evaluated using the RMSE and MAE. The results showed that, ARIMA (2, 1, 1) x SARIMA (2, 1, 1)12 is the best forecasting model followed by ARIMA (2, 1, 1) and ARMA (2, 1) on Nigeria monthly Treasury Bills.
       
  • Automation of Balanced Nested Design; NeDPy

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 1Marcel Tochukwu Obinna, Uchenna Petronilla Ogoke, Ethelbert Chinaka NdukaThis work was done considering the principle of automating nested designs. It was aimed at developing a user friendly statistical package (NeDPy) that can be used to analyse experiment that has nested factor(s). NeDPy was coined from “NESTED DESIGN PYTHON” and was developed using python programming language. Python modules like NumPy, Scipy, Matplotlib, Tkinter etc. was used to develop a user-friendly app with GUI (graphical user interface) that can analyse a two-stage and three-stage nested design to produce all relevant information. These include, indicating significant factor(s), creating ANOVA table, giving estimate for model and variance component, descriptive analysis, generating the residuals of the data set, drawing diagnostic plots like normal probability plot, box plot etc. NeDPy was used to solve problems from some cited sources where the problem has been solved both manually and using some trusted software. Some important results were compared and found to be identical. This validates NeDPy and makes it a recommendable statistical package for analysing nested design.
       
  • The Study of HIV/AIDS Trend in Yobe State for the Prescribed Period (1999
           – 2019)

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 1Chiwa Musa Dalah, V. V. Singh, Ibrahim Abdullahi, A. A. SuleimanThe effect of the Human Immunodeficiency Virus/Acquired Immune deficiency syndrome (HIV/AIDS) global epidemic continue to emerge decades after the first wave of infection. Since the start of the epidemic, many measures have been taken by the government and non-governmental organizations to control the outbreak. In Yobe State, the programs implemented include enlightenment, HIV/AIDS testing, and counseling, free drugs, and therapy. The State is mainly an agricultural state created out of the old Borno State on 27 August 1991. With an estimated population of about 2.5 Million, Yobe state covers a total of 54, 428sq km land area, the state borders the Nigerian states of Bauchi, Borno, Gombe, and Jigawa. It borders the Diffa Region and Zinder Region to the north in the Republic of Niger. Because the state lies mainly in the dry savanna belt, the State is dry and hot for most of the year except in the southern part of the state, which has a milder climate. This study has looked at the trend of the epidemic in the state. Statistical time series trends were used in analyzing the data. Three methods of fitting trend of a time series data namely, linear trend, quadratic trend and exponential trend were employed to fit the data of HIV patients on ART. The linear trend model has MAPE, MAD and MSD values of 24.8, 147.5 and 31767.8 respectively. The quadratic model provides respective accuracy measures as MAPE=21.6, MAD=138.8 and MSD=26780.5. An exponential model gives MAPE=22.4, MAD=144.7 and MSD=29265.7. The result indicated that the quadratic model with the smallest accuracy measures have been the best and most suitable mathematical model to fit the dataset.
       
  • On the Efficiency of Multiple Linear Regression over Artificial Neural
           Network Models

    • Abstract: Publication year: 2020Source: International Journal of Statistics and Applications, Volume 10, Number 1Asogwa O. C., Eze N. M., Eze C. M., Okonkwo C. I., Ojide K. C.There has been a considerable and continuous interest to develop models for rapid and accurate modeling of students’ academic performances. In this study, an Artificial Neural Network model (ANNm) and a Multiple Linear Regression model (MLRm) were used to model the academic performance of university students. The accuracy of the models was judged by model evaluation criteria like and The modeling ability of the developed ANN model architecture was compared with a MLR model using the same training data sets. The squared regression coefficients of prediction for MLR and ANN models were 0.746 and 0.893, respectively. The results revealed that ANN model proved more accurate in modeling the data set, as compared with MLR model. This was because ANN model had its as against the traditional model which it’s was 0.182. Based on the results of this study, ANN model could be used as a promising approach for rapid modeling and prediction in the academic fields.
       
  • Forecasting Inflation Rates Using Artificial Neural Networks

    • Abstract: Publication year: 2019Source: International Journal of Statistics and Applications, Volume 9, Number 6Akintunde Mutairu Oyewale, Agunloye Oluokun Kasali, Kgosi Phazamile M., Michael Vincent Abiodun, Eriobu Nkiru Obioma, Abdulazeez Ismail AdeyinkaAccuracy and reliability in forecasting the inflation rates or predicting it trend correctly is very importance for would be investors, academia, and policy makers. The use of intelligence based model have been found to be invaluable for forecasting financial and economic series like inflation rates exchange rates and stock bond so to mention the few. Researchers have used several parametric models in forecasting exchange rates and other financial and economics data. This paper therefore employs the use of non-parametric approach (artificial neural networks) in forecasting inflation rates. It is an indubitable fact that Artificial Neural networks (ANNs), emulates the information processing capabilities of neurons of the human brain. It uses a distributed representation of the information stored in the networks, and thus resulting in robustness against damage and corresponding fault tolerance. A major advantage of neural networks is their ability to provide flexible mapping between inputs and outputs. The arrangement of the simple units into a multi-layer frame works produces a map between inputs and outputs that is consistent with any underlying functional relationship irrespective of the true functional form. This paper therefore, used three artificial neural networks (Standard Backpropagation (SBP), Scaled Conjugate Gradient (SCG) and Backpropagation based forecasting model for Nigerian and American inflation rates. These models were evaluated using five performance series and a comparison was made with traditional ARIMA models. Inflation rates data of United States of America and Federal Republic of Nigeria were used for empirical illustration. The data were analyzed using both statistical programme for social science (SPSS) and Econometrics view (E-view). The results obtained show that all the ANN models outperformed ARIMA models. The implication of this is that ANN based model can be used to forecast the inflation rates market structure.
       
 
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