Colombian Women’s Life Patterns: A Multivariate Density Regression Approach

Women in Colombia face difficulties related to the patriarchal traits of their societies and well-known conflict afflicting country since 1948. In this critical context, our aim is study relationship between baseline socio-demographic factors variables associated fertility, partnership patterns, work activity. To best exploit explanatory structure, we propose a Bayesian multivariate density regression model, which can accommodate mixed responses with censored, constrained, binary traits. The flexible nature models allows for nonlinear functions non-standard features errors, such as asymmetry or multi-modality. model has interpretable covariate-dependent weights constructed through normalization, allowing combinations categorical continuous covariates. Computational inference are overcome an adaptive truncation algorithm combining Metropolis-Hastings sequential Monte Carlo create sequence automatically truncated posterior mixtures. For on Colombian women’s life variety quantities visualised described, particular, findings highlight detrimental impact family violence choices behaviors.