Pub Date : 2020-01-01DOI: 10.3844/jmssp.2020.233.238
Santosh Ghimire
In this article, we establish some inequalities associated to a sequence of dyadic martingales. These inequalities are sub-Gaussian type estimates. We derive the inequalities for a regular sequence of dyadic martingales and also for a tail sequence.
{"title":"Inequalities Associated to a Sequence of Dyadic Martingales","authors":"Santosh Ghimire","doi":"10.3844/jmssp.2020.233.238","DOIUrl":"https://doi.org/10.3844/jmssp.2020.233.238","url":null,"abstract":"In this article, we establish some inequalities associated to a sequence of dyadic martingales. These inequalities are sub-Gaussian type estimates. We derive the inequalities for a regular sequence of dyadic martingales and also for a tail sequence.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"29 1","pages":"233-238"},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82678061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.3844/jmssp.2020.198.211
T. N. Dhamala, S. Gupta, D. Khanal, Urmila Pyakurel
Routing of more than one different commodity from specific origin nodes to the corresponding destination nodes through the arcs of an underlying network respecting the capacity constraints is one of the main problems in operational research. Among them, the quickest multi-commodity flow problem concerns with minimization of time taken to complete this process. The general multi-commodity and quickest multi-commodity flow problems are computationally hard. By flipping the orientation of lanes towards the demand nodes, the outbound lane capacities are increases. We introduce lane reversals in the quickest multi-commodity flow problem and present two approximation algorithms, one polynomial-time with the help of length-bounded flow and another FPTAS by using ∆-condensed time-expanded graph. Both algorithms prevent reversing arc capacities that are not required by the optimal flows that may be of interest for other purposes.
{"title":"Quickest Multi-Commodity Flow Over Time with Partial Lane Reversals","authors":"T. N. Dhamala, S. Gupta, D. Khanal, Urmila Pyakurel","doi":"10.3844/jmssp.2020.198.211","DOIUrl":"https://doi.org/10.3844/jmssp.2020.198.211","url":null,"abstract":"Routing of more than one different commodity from specific origin nodes to the corresponding destination nodes through the arcs of an underlying network respecting the capacity constraints is one of the main problems in operational research. Among them, the quickest multi-commodity flow problem concerns with minimization of time taken to complete this process. The general multi-commodity and quickest multi-commodity flow problems are computationally hard. By flipping the orientation of lanes towards the demand nodes, the outbound lane capacities are increases. We introduce lane reversals in the quickest multi-commodity flow problem and present two approximation algorithms, one polynomial-time with the help of length-bounded flow and another FPTAS by using ∆-condensed time-expanded graph. Both algorithms prevent reversing arc capacities that are not required by the optimal flows that may be of interest for other purposes.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"104 1","pages":"198-211"},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78358740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.3844/jmssp.2020.142.147
Phanindra Prasad Bhandari, S. Khadka, Stefan Ruzika, Luca E. Schäfer
We consider an evacuation planning problem in the sense of computing a feasible dynamic flow lexicographically maximizing the amount of flow entering a set of terminals with respect to a given prioritization and given vertex capacities. We propose a polynomial time algorithm for the static version of the problem and a pseudo-polynomial time algorithm for the dynamic case. We show that by neglecting the vertex capacities, the dynamic version can be solved in polynomial time by using temporally repeated flows.
{"title":"Lexicographically Maximum Dynamic Flow with Vertex Capacities","authors":"Phanindra Prasad Bhandari, S. Khadka, Stefan Ruzika, Luca E. Schäfer","doi":"10.3844/jmssp.2020.142.147","DOIUrl":"https://doi.org/10.3844/jmssp.2020.142.147","url":null,"abstract":"We consider an evacuation planning problem in the sense of computing a feasible dynamic flow lexicographically maximizing the amount of flow entering a set of terminals with respect to a given prioritization and given vertex capacities. We propose a polynomial time algorithm for the static version of the problem and a pseudo-polynomial time algorithm for the dynamic case. We show that by neglecting the vertex capacities, the dynamic version can be solved in polynomial time by using temporally repeated flows.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"40 1","pages":"142-147"},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74013395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.3844/jmssp.2020.148.160
Eman A. El-Dessouky Nassef
Warranty one of the main factors which effect on the decision to purchase any product whether it is non repairable or repairable, therefore, in market the manufacturers can compete by using warranty service. The cost of warranty are wanted to predict which are mirrored on the price and profitability of products. To achieve this goal, the research is concerned with predicting the cost of the two common types of warranty models which are free rebate warranty and pro-rata rebate warranty when The lifetime of items is assumed to follow Dagum distribution. The constant stress partially accelerated life tests based on type II censoring is used. Maximum likelihood method is used to estimate the model parameters and acceleration factor of lifetime distribution from the test data. Confidence Interval for the model parameters are constructed using normal approximation and bootstrap method. Finally, Some numerical illustrations are provided.
{"title":"Warranty Cost Models using Accelerated Life Tests on Dagum Distribution","authors":"Eman A. El-Dessouky Nassef","doi":"10.3844/jmssp.2020.148.160","DOIUrl":"https://doi.org/10.3844/jmssp.2020.148.160","url":null,"abstract":"Warranty one of the main factors which effect on the decision to purchase any product whether it is non repairable or repairable, therefore, in market the manufacturers can compete by using warranty service. The cost of warranty are wanted to predict which are mirrored on the price and profitability of products. To achieve this goal, the research is concerned with predicting the cost of the two common types of warranty models which are free rebate warranty and pro-rata rebate warranty when The lifetime of items is assumed to follow Dagum distribution. The constant stress partially accelerated life tests based on type II censoring is used. Maximum likelihood method is used to estimate the model parameters and acceleration factor of lifetime distribution from the test data. Confidence Interval for the model parameters are constructed using normal approximation and bootstrap method. Finally, Some numerical illustrations are provided.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"336 1","pages":"148-160"},"PeriodicalIF":0.3,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76383812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-08DOI: 10.3844/JMSSP.2019.185.195
H. Simiyu, A. Waititu, Jane Aduda Akinyi
In the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy generates a more robust model. This is to say that the nonexistence of input selection criteria notwithstanding, the models have been developed without due consideration to the effect that the choice of input selection technique would have on model complexity, learning difficulty and performance measures. In this study, we deviate from the conventional techniques applied by the pure ANN option price models and adopt the hybrid model in which the volatility component is handled using some celebrated time series models, with speci?city to the ANN-GJR-GARCH model - a hybrid of the ANN and a time series hybrid. The hybrid ANN option pricing model is then framed and tested with the forecasts of the ANN-GJR-GARCH model as a volatility input alongside two other inputs - time to maturity and moneyness. Finally, we compare the performance of the hybrid model developed with that of a pure ANN model. Results indicate that the hybrid model outperforms the pure ANN model not only in forecasting but also in the training time and model complexity.
{"title":"A Hybrid Artificial Neural Network Model for Option Pricing","authors":"H. Simiyu, A. Waititu, Jane Aduda Akinyi","doi":"10.3844/JMSSP.2019.185.195","DOIUrl":"https://doi.org/10.3844/JMSSP.2019.185.195","url":null,"abstract":"In the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy generates a more robust model. This is to say that the nonexistence of input selection criteria notwithstanding, the models have been developed without due consideration to the effect that the choice of input selection technique would have on model complexity, learning difficulty and performance measures. In this study, we deviate from the conventional techniques applied by the pure ANN option price models and adopt the hybrid model in which the volatility component is handled using some celebrated time series models, with speci?city to the ANN-GJR-GARCH model - a hybrid of the ANN and a time series hybrid. The hybrid ANN option pricing model is then framed and tested with the forecasts of the ANN-GJR-GARCH model as a volatility input alongside two other inputs - time to maturity and moneyness. Finally, we compare the performance of the hybrid model developed with that of a pure ANN model. Results indicate that the hybrid model outperforms the pure ANN model not only in forecasting but also in the training time and model complexity.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"25 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87174358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-25DOI: 10.3844/JMSSP.2019.176.184
L. Ricci, G. Boggio
Multivariate exponential dispersion models (MEDMs) were defined in 2013 by Jorgensen and Martinez. A particular case of MEDM is the bivariate Gamma model; in this article we prove that, under certain conditions, this is a limit distribution for MEDM generated by bivariate regularly varying measures, extending a previous result given by the aforementioned authors for the univariate case. As necessary tools for proving the main result, we use bivariate regularly varying functions and bivariate regularly varying measures; we also state a bivariate version of Tauberian Karamata’s theorems and a particular Karamata representation of bivariate slowly varying functions.
{"title":"A Convergence Theorem for Bivariate Exponential Dispersion Models","authors":"L. Ricci, G. Boggio","doi":"10.3844/JMSSP.2019.176.184","DOIUrl":"https://doi.org/10.3844/JMSSP.2019.176.184","url":null,"abstract":"Multivariate exponential dispersion models (MEDMs) were defined in 2013 by Jorgensen and Martinez. A particular case of MEDM is the bivariate Gamma model; in this article we prove that, under certain conditions, this is a limit distribution for MEDM generated by bivariate regularly varying measures, extending a previous result given by the aforementioned authors for the univariate case. As necessary tools for proving the main result, we use bivariate regularly varying functions and bivariate regularly varying measures; we also state a bivariate version of Tauberian Karamata’s theorems and a particular Karamata representation of bivariate slowly varying functions.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"42 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79508961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-24DOI: 10.3844/JMSSP.2019.112.121
Asif R Khan, F. Mehmood
We provide double weighted integrals identities of Montgomery for differentiable function of higher order for two variables and by help of those identities we get generalization of Ostrowski and Gruss type inequalities for weighted integrals for differentiable functions of higher order for two variables.
{"title":"Double Weighted Integrals Identities of Montgomery for Differentiable Function of Higher Order","authors":"Asif R Khan, F. Mehmood","doi":"10.3844/JMSSP.2019.112.121","DOIUrl":"https://doi.org/10.3844/JMSSP.2019.112.121","url":null,"abstract":"We provide double weighted integrals identities of Montgomery for differentiable function of higher order for two variables and by help of those identities we get generalization of Ostrowski and Gruss type inequalities for weighted integrals for differentiable functions of higher order for two variables.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"63 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86269467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.3844/JMSSP.2019.158.175
H. Simiyu, A. Waititu, Jane Aduda Akinyi
Option pricing using artificial neural networks (ANN) model while relaxing the assumption of constant volatility still remains a challenge. The conventional practice for pure ANN models has been to either model volatility using the very ANN model and have the model output fed as an input to the ANN option pricing model, or to make allowances for a large number of lags directly as inputs to the option pricing model with the belief that the ability of ANN to incorporate flexibility and redundancy creates a more robust model. This has been done in spite of a well-known fact-that financial time series data harbors a set of characteristics such as volatility clustering, leptokurtosis and leverage effects-features that ANNs in their pure forms have proved inadequate in capturing. Consequently, this study sought to follow the conventional methods employed by other studies and developed two pure ANN option pricing models-one with constant volatility and the other while violating the assumption of constant volatility with an aim of establishing whether significant differences exist in the outputs of the two models. The intraday data for the AAPL stock option for the period between December 2016 and March 2017 with 56,238 data points was used in validating the developed models. Results indicate that the ANN model (with varying volatility) makes better predictions than the model with constant volatility. However, the difference between the performance of the two models is not significant at 0.05 level of significance.
{"title":"Comparative Analysis of the Artificial Neural Networks Options Pricing Model Under Constant and Time-Variant Volatilities","authors":"H. Simiyu, A. Waititu, Jane Aduda Akinyi","doi":"10.3844/JMSSP.2019.158.175","DOIUrl":"https://doi.org/10.3844/JMSSP.2019.158.175","url":null,"abstract":"Option pricing using artificial neural networks (ANN) model while relaxing the assumption of constant volatility still remains a challenge. The conventional practice for pure ANN models has been to either model volatility using the very ANN model and have the model output fed as an input to the ANN option pricing model, or to make allowances for a large number of lags directly as inputs to the option pricing model with the belief that the ability of ANN to incorporate flexibility and redundancy creates a more robust model. This has been done in spite of a well-known fact-that financial time series data harbors a set of characteristics such as volatility clustering, leptokurtosis and leverage effects-features that ANNs in their pure forms have proved inadequate in capturing. Consequently, this study sought to follow the conventional methods employed by other studies and developed two pure ANN option pricing models-one with constant volatility and the other while violating the assumption of constant volatility with an aim of establishing whether significant differences exist in the outputs of the two models. The intraday data for the AAPL stock option for the period between December 2016 and March 2017 with 56,238 data points was used in validating the developed models. Results indicate that the ANN model (with varying volatility) makes better predictions than the model with constant volatility. However, the difference between the performance of the two models is not significant at 0.05 level of significance.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"19 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73863793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.3844/JMSSP.2019.79.85
N. Faried, Z. A. Hassanain, H. A. Ghaffar, A. Lokman
The idea of multiplying a formal Taylor power series by z to make a right shift operator on the space of all square summable sequences of real numbers was due to A.L. Shield. In this work, we consider Taylor power series in m-variables and we give upper and lower estimations of s-numbers for multiplication of m- right weighted shift operators. This allowed us to estimate upper bounds for s-numbers of infinite series of m-right weighted shift operators and give some applications.
{"title":"S-Numbers of Weighted Shift Operators on P-Summable Formal Entire Functions of M-Variables","authors":"N. Faried, Z. A. Hassanain, H. A. Ghaffar, A. Lokman","doi":"10.3844/JMSSP.2019.79.85","DOIUrl":"https://doi.org/10.3844/JMSSP.2019.79.85","url":null,"abstract":"The idea of multiplying a formal Taylor power series by z to make a right shift operator on the space of all square summable sequences of real numbers was due to A.L. Shield. In this work, we consider Taylor power series in m-variables and we give upper and lower estimations of s-numbers for multiplication of m- right weighted shift operators. This allowed us to estimate upper bounds for s-numbers of infinite series of m-right weighted shift operators and give some applications.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"32 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82254270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.3844/JMSSP.2019.225.232
J. E. Ruiz-Castro
A complex multi-state system subject to wear failure and given preventive maintenance is considered. Various internal levels of degradation are assumed. The repair facility is composed of a repairperson, who may take one or more vacations during the period considered. A policy is established for the repairperson’s vacation time. Two types of task may be performed by the repairperson: corrective repair and preventive maintenance. All embedded times in the system are phase type distributed. The transient and stationary distributions are determined and several reliability measures are developed in a matrix-algorithmic form. Costs and rewards are included in the model. The results are implemented computationally with Matlab. A numerical example shows that the distribution of vacation time can be optimised according to the net reward established.
{"title":"A Complex Multi-State System with Vacations in the Repair","authors":"J. E. Ruiz-Castro","doi":"10.3844/JMSSP.2019.225.232","DOIUrl":"https://doi.org/10.3844/JMSSP.2019.225.232","url":null,"abstract":"A complex multi-state system subject to wear failure and given preventive maintenance is considered. Various internal levels of degradation are assumed. The repair facility is composed of a repairperson, who may take one or more vacations during the period considered. A policy is established for the repairperson’s vacation time. Two types of task may be performed by the repairperson: corrective repair and preventive maintenance. All embedded times in the system are phase type distributed. The transient and stationary distributions are determined and several reliability measures are developed in a matrix-algorithmic form. Costs and rewards are included in the model. The results are implemented computationally with Matlab. A numerical example shows that the distribution of vacation time can be optimised according to the net reward established.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"33 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79086561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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