Aim & Scope
Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis ) was first published in 1985 publishing contributions in the interface between stochastic modelling data analysis and their applications in business finance insurance management and production. The main objective is to publish papers both technical and practical presenting new results which solve real-life problems or have great potential in doing so. A second objective is to present new methods for solving such problems i.e. optimization data base management knowledge acquisition expert systems computer-aided decision supports and neural computing. The scope of the journal is now broadened both in supporting topics and in appropriate methodology. Topics to be added include managerial processes reliability quality control data analysis and data mining. New methodologies include wavelets Markov-chain Monte Carlo methods and spatial statistics. [1]
Continuations / Journal History
| ( 1985 - 1999 ) | Applied Stochastic Models and Data Analysis (ASMDA) | ( 1999 - 9999 ) | Applied Stochastic Models in Business and Industry |
2024
An EM‐based likelihood inference for degradation data analysis using gamma process
L Palayangoda , N Balakrishnan
Applied Stochastic Models in Business and Industry , 2024
X Han , B Wei , H Yang , Q Zhao
Applied Stochastic Models in Business and Industry , 2024
A new extended δ‐shock model with the consideration of shock magnitude
Applied Stochastic Models in Business and Industry , 2024
L Bautista , I Castro , C Bérenguer , ... , L Doyen
Applied Stochastic Models in Business and Industry , 2024
On optimal allocation of redundancies in random weighted k$$ k $$‐out‐of‐n$$ n $$ systems
Applied Stochastic Models in Business and Industry , 2024
Optimal designs of accelerated degradation tests with random shock failures and measurement errors
Applied Stochastic Models in Business and Industry , 2024
Estimation of VaR with jump process: Application in corn and soybean markets
M Lin , I SenGupta , W Wilson
Applied Stochastic Models in Business and Industry , 2024