A finite mixture model is well-known in statistics due to its versatility and is being actively researched. This paper reviews finite mixture model literature via bibliometric analysis, focusing on the trend and link between finite mixture model studies. The bibliometric analysis consists of four main phases; formulating research questions, locating research, research selection, evaluation, and analyzing and synthesizing selected papers. There are 667 journal articles extracted from the Web of Science (WoS) database from publications within 1988 to 2020. The Biblioshiny with R packages and VOSViewer were used as analytical tools. The findings show that there is an increasing trend of annual publication on the finite mixture model study. The results also outline key journals and the highest cited articles. Network analysis was also conducted and explored in scientific cooperation in the finite mixture model study. This study proposed a research agenda in the finite mixture model by identifying its current state and population trends.

This study involved a systematic literature review using bibliometric analysis to examine the evolution and current trends of Markov switching studies. The bibliometric analysis was used for the descriptive, intellectual, social, and conceptual network analyses, while systematic reviews were used to identify the application of the Markov switching model. A total of 449 articles were selected and extracted from the Web of Science (WoS) between 1992 and 2021. The publication trends, most influential countries and articles, leading journals, collaboration networks, research hotspots, research fronts, coupling networks, and application of the model in various disciplines were described. This study summarized the research agenda of the Markov switching field, which would be helpful for researchers and funding agencies.