SLTCA: Scalable and Robust Latent Trajectory Class Analysis Using Artificial Likelihood. The package is on CRAN now. This repository will mainly serve as a platform for bug reporting (at Issues) while we will post the lastest version on CRAN. To access the latest version on GitHub, please go to branch CRAN.

Our method supports lon-gitudinal continuous, binary and count data. For more methodological details, please re-fer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class anal-ysis using artificial likelihood. Biometrics <doi:10.1111/biom.13366>. Simulate a dataset with longitudinal observations. Sample size.

2021年1月13日 · Conduct latent trajectory class analysis with longitudinal observations.

载荷齿接触分析（LTCA）一直是螺旋锥齿轮和准双曲面齿轮的重要接触机械性能优化技术。 为了与基于经济软件包的常规模拟负载齿接触分析（SLTCA）区别开来，开发了数值负载齿接触分析（NLTCA）及其创新的半分析确定方法。 在充分考虑齿面弯曲行为特征的情况下，进行了双曲线壳有限元建模，然后将改进的齿接触分析（TCA）应用于数据驱动的负载齿接触点的确定。 然后，除了全局边界条件之外，还研究了准确的局部边界条件。 尤其是，考虑到计算精度和效 …

Conduct latent trajectory class analysis with longitudinal data. Our method supports longitudinal continuous, binary and count data. For more methodological details, please refer to Hart, K.R., …

SLTCA: Scalable and Robust Latent Trajectory Class Analysis Using Artificial Likelihood - SLTCA/DESCRIPTION at master · tengfei-emory/SLTCA

2021年1月13日 · Simulate a dataset with longitudinal observations. Sample size. Returns a data frame with 6 longitudinal features y.1 - y.6, including count (y.1 and y.2), binary (y.3 and y.4) and continuous (y.5 and y.6) type. Variable baselinecov is the baseline risk factor of latent classes. Variable latent is the true latent class labels. Teng Fei.

Conduct latent trajectory class analysis with longitudinal data. Our method supports longitudinal continuous, binary and count data. For more methodological details, please refer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class analysis using artificial likelihood. Biometrics <doi:10.1111/biom.13366>.

SLTCA: Scalable and Robust Latent Trajectory Class Analysis Using Artificial Likelihood. The package is on CRAN now. This repository will mainly serve as a platform for bug reporting (at Issues) while we will post the lastest version on CRAN. To access the latest version on GitHub, please go to branch CRAN.

2021年1月13日 · Conduct latent trajectory class analysis with longitudinal data. Our method supports longitudinal continuous, binary and count data. For more methodological details, please refer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class analysis using artificial likelihood. Biometrics <doi:10.1111/biom.13366>.