以Web of Science核心合集数据库中的SCI和SSCI引文索引收录的发表于1900-2021年的521篇英文文献为研究样本,使用CiteSpace和VOSviewer定量化分析工具呈现了近十多年来预测心智研究的时空分布、研究热点和前沿问题,而后从人类高级认知...以Web of Science核心合集数据库中的SCI和SSCI引文索引收录的发表于1900-2021年的521篇英文文献为研究样本,使用CiteSpace和VOSviewer定量化分析工具呈现了近十多年来预测心智研究的时空分布、研究热点和前沿问题,而后从人类高级认知加工、神经科学技术和特殊群体三个方面分析了预测心智研究未来的发展趋势和方向。研究发现,预测心智研究发文量整体上呈现持续上升的趋势;英国是预测心智的主要研究国度;心理学和神经科学是预测心智主要的研究领域;从最初关注内感觉过渡到人类高级认知加工是预测心智发展的必然结果,借助神经科学技术可以清晰地再现大脑进行层级预测编码和错误预测最小化的过程,以特殊群体作为切入点也是预测心智研究的一个前沿趋势。展开更多
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
文摘以Web of Science核心合集数据库中的SCI和SSCI引文索引收录的发表于1900-2021年的521篇英文文献为研究样本,使用CiteSpace和VOSviewer定量化分析工具呈现了近十多年来预测心智研究的时空分布、研究热点和前沿问题,而后从人类高级认知加工、神经科学技术和特殊群体三个方面分析了预测心智研究未来的发展趋势和方向。研究发现,预测心智研究发文量整体上呈现持续上升的趋势;英国是预测心智的主要研究国度;心理学和神经科学是预测心智主要的研究领域;从最初关注内感觉过渡到人类高级认知加工是预测心智发展的必然结果,借助神经科学技术可以清晰地再现大脑进行层级预测编码和错误预测最小化的过程,以特殊群体作为切入点也是预测心智研究的一个前沿趋势。
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.
