We propose to determine the underlying causal structure of the elements of happiness from a set of empirically obtained data based on Bayesian. We consider the proposal to study happiness as a multidimensional constru...We propose to determine the underlying causal structure of the elements of happiness from a set of empirically obtained data based on Bayesian. We consider the proposal to study happiness as a multidimensional construct which converges four dimensions with two different Bayesian techniques, in the first we use the Bonferroni correction to estimate the mean multiple comparisons, on this basis it is that we use the function t and a z-test, in both cases the results do not vary, so it is decided to present only those shown by the t test. In the Bayesian Multiple Linear Regression, we prove that happiness can be explained through three dimensions. The technical numerical used is MCMC, of four samples. The results show that the sample has not atypical behavior too and that suitable modifications can be described through a test. Another interesting result obtained is that the predictive probability for the case of sense positive of life and personal fulfillment dimensions exhibit a non-uniform variation.展开更多
Here,we introduce a novel framework for modelling the spatiotemporal dynamics of disease spread known as conditional logistic individual-level models(CL-ILM's).This framework alleviates much of the computational b...Here,we introduce a novel framework for modelling the spatiotemporal dynamics of disease spread known as conditional logistic individual-level models(CL-ILM's).This framework alleviates much of the computational burden associated with traditional spatiotemporal individual-level models for epidemics,and facilitates the use of standard software for fitting logistic models when analysing spatiotemporal disease patterns.The models can be fitted in either a frequentist or Bayesian framework.Here,we apply the new spatial CL-ILM to simulated data,semi-real data from the UK 2001 foot-and-mouth disease epidemic,and real data from a greenhouse experiment on the spread of tomato spotted wilt virus.展开更多
文摘We propose to determine the underlying causal structure of the elements of happiness from a set of empirically obtained data based on Bayesian. We consider the proposal to study happiness as a multidimensional construct which converges four dimensions with two different Bayesian techniques, in the first we use the Bonferroni correction to estimate the mean multiple comparisons, on this basis it is that we use the function t and a z-test, in both cases the results do not vary, so it is decided to present only those shown by the t test. In the Bayesian Multiple Linear Regression, we prove that happiness can be explained through three dimensions. The technical numerical used is MCMC, of four samples. The results show that the sample has not atypical behavior too and that suitable modifications can be described through a test. Another interesting result obtained is that the predictive probability for the case of sense positive of life and personal fulfillment dimensions exhibit a non-uniform variation.
基金funded by an Alberta Innovates Graduate Student Scholarship for Data-Enabled Innovation and a Uni-versity of Calgary Eyes High Doctoral Scholarship,Doctoral Completion Scholarship,Natural Sciences and Engineering Research Council of Canada(NSERC)Discovery Grants program(RGPIN/03292-2022)and the Alberta Innovates Advance-NSERC Alliance program(222302037).
文摘Here,we introduce a novel framework for modelling the spatiotemporal dynamics of disease spread known as conditional logistic individual-level models(CL-ILM's).This framework alleviates much of the computational burden associated with traditional spatiotemporal individual-level models for epidemics,and facilitates the use of standard software for fitting logistic models when analysing spatiotemporal disease patterns.The models can be fitted in either a frequentist or Bayesian framework.Here,we apply the new spatial CL-ILM to simulated data,semi-real data from the UK 2001 foot-and-mouth disease epidemic,and real data from a greenhouse experiment on the spread of tomato spotted wilt virus.
