statistical_modeling/README.md

Statistical Modeling

This section of the dataset contains sparse matrices related to statistical modeling. More specifically, this contain precision matrices as used within the integrated nested Laplace approximation (INLA) framework.

temp_prior_st1

Domain: Prior precision matrix from spatio-temporal statistical modeling applied to temperature prediction

Caracteristics

• Type: positive-definite symmetric
• Size: 1000506x1000506, 50870502 nnz
• Used in: Linear system solving

	Initial	Cholesky	Fill-in	Depth
temp_prior_st1	50870502
RCM
AMD
ND

References

• Integrated Nested Laplace Approximations for Large-Scale Spatiotemporal Bayesian Modeling

temp_conditional_st1

Domain: Conditional precision matrix from spatio-temporal statistical modeling applied to temperature prediction

Caracteristics

• Type: positive-definite symmetric
• Size: 1000506x1000506, 62837532 nnz
• Used in: Linear system solving, Selected linear system solving

	Initial	Cholesky	Fill-in	Depth
temp_conditional_st1	62837532
RCM
AMD
ND

References

• Integrated Nested Laplace Approximations for Large-Scale Spatiotemporal Bayesian Modeling

airpoll_prior_st3

Domain: Prior precision matrix from a coregional (trivariate) spatio-temporal statistical modeling applied to air pollution

Caracteristics

• Type: positive-definite symmetric
• Size: 8499x8499, 1205931 nnz
• Used in: Linear system solving
• | | Initial | Cholesky | Fill-in | Depth |

|-------------------|---------|----------|---------|-------| | airpoll_prior_st3 | 1205931 | | | | | RCM | | | | | | AMD | | | | | | ND | | | | |

References

• Multivariate disaggregation modeling of air pollutants: a case-study of PM2.5, PM10 and ozone prediction in Portugal and Italy

airpoll_conditional_st3

Domain: Conditional precision matrix from a coregional (trivariate) spatio-temporal statistical modeling applied to air pollution

Caracteristics

• Type: positive-definite symmetric
• Size: 8499x8499, 1218651 nnz
• Used in: Linear system solving, Selected linear system solving

	Initial	Cholesky	Fill-in	Depth
airpoll_conditional_st3	1218651
RCM
AMD
ND

References

• Multivariate disaggregation modeling of air pollutants: a case-study of PM2.5, PM10 and ozone prediction in Portugal and Italy