Computational Mathematics and Statistics are quite broad areas having applications in almost all the areas of science and engineering. It is so because they have the universal applicability in modeling real life situations. In other words, we can call them as natural languages for describing the laws of mathematical physics having the capability of understanding and interpreting the underlying results.
Advancement in these areas reflects the development of algorithms and then implementing them to produce successful computational techniques. It involves knowledge of programming languages, data collection, hypothesis testing along with various mathematical and statistical tools. Nowadays emerging fields such as Data science, machine learning, artificial intelligence etc. are also related areas of development in advances in computational Mathematics and Statistics.
Basic target of this Research Topic is to have a collection of original and high quality manuscripts from the researchers/academicians discussing various case studies related to natural science, basic science and engineering etc. Topics of interest include but are not limited to the followings:
- Mathematical Modelling and simulation
- Estimation methods
- Data analysis
- Image processing
- Reliability inference
- Statistical modelling
- Applications in health sciences and social sciences etc.
When we talk about Advances in computational Mathematics and Statistics, it is widely used to describe complex models in various fields. In this direction, a lot of progress all over the world is going on to solve various models with the help of a large variety of approaches. For this reason, they have been proved quite beneficial in studying and analysing even a large amount of data under consideration. It also involves interpretation of the results obtained and their processing through statistical tools.
This Research Topic welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
This Research Topic “Advances in computational Mathematics and Statistics’’ is specially meant for the researchers/academicians involved in the area of computational aspects either via mathematical or statistical approach. We accept both reviews, expository and original research articles dealing with the recent advances in the computational methodology or novel scientific application areas or both. Research work dealing with the development of new techniques must make sure that the work done rely on rigorous analysis and results produced are convincing.
Computational Mathematics and Statistics are quite broad areas having applications in almost all the areas of science and engineering. It is so because they have the universal applicability in modeling real life situations. In other words, we can call them as natural languages for describing the laws of mathematical physics having the capability of understanding and interpreting the underlying results.
Advancement in these areas reflects the development of algorithms and then implementing them to produce successful computational techniques. It involves knowledge of programming languages, data collection, hypothesis testing along with various mathematical and statistical tools. Nowadays emerging fields such as Data science, machine learning, artificial intelligence etc. are also related areas of development in advances in computational Mathematics and Statistics.
Basic target of this Research Topic is to have a collection of original and high quality manuscripts from the researchers/academicians discussing various case studies related to natural science, basic science and engineering etc. Topics of interest include but are not limited to the followings:
- Mathematical Modelling and simulation
- Estimation methods
- Data analysis
- Image processing
- Reliability inference
- Statistical modelling
- Applications in health sciences and social sciences etc.
When we talk about Advances in computational Mathematics and Statistics, it is widely used to describe complex models in various fields. In this direction, a lot of progress all over the world is going on to solve various models with the help of a large variety of approaches. For this reason, they have been proved quite beneficial in studying and analysing even a large amount of data under consideration. It also involves interpretation of the results obtained and their processing through statistical tools.
This Research Topic welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
This Research Topic “Advances in computational Mathematics and Statistics’’ is specially meant for the researchers/academicians involved in the area of computational aspects either via mathematical or statistical approach. We accept both reviews, expository and original research articles dealing with the recent advances in the computational methodology or novel scientific application areas or both. Research work dealing with the development of new techniques must make sure that the work done rely on rigorous analysis and results produced are convincing.
