SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© Thomson Reuters Journal Citation Reports 2015
To calculate the five year Impact Factor, citations are counted in 2014 to the previous five years and divided by the source items published in the previous five years.
© Journal Citation Reports 2015, Published by Thomson Reuters
The Journal of Statistical Planning and Inference offers itself as a multifaceted and all-inclusive bridge between classical aspects of statistics and probability, and the emerging interdisciplinary aspects that have a potential of revolutionizing the subject. While we maintain our traditional strength in statistical inference, design, classical probability, and large sample methods, we also have a far more inclusive and broadened scope to keep up with the new problems that confront us as statisticians, mathematicians, and scientists.
We publish high quality articles in all branches of statistics, probability, discrete mathematics, machine learning, and bioinformatics. We also especially welcome well written and up to date review articles on fundamental themes of statistics, probability, machine learning, and general biostatistics. Thoughtful letters to the editors, interesting problems in need of a solution, and short notes carrying an element of elegance or beauty are equally welcome.
We want to serve as the broadest international platform for high quality research on every aspect of our field, traditional and cutting edge. The quality and the breadth of our editorial board reflects that singular priority.