Fits a multivariable Mendelian randomization model adjusting for weak instruments. The functions requires a formatted dataframe using the `format_mvmr`

function, as well a phenotypic correlation matrix `pcor`

. This should be obtained from individual level
phenotypic data, or constructed as a correlation matrix where correlations have previously been reported. Confidence intervals are calculated using a non-parametric bootstrap.
By default, standard errors are not produced but can be calculated by setting `se = TRUE`

. The number of bootstrap iterations is specified using the `iterations`

argument.
Note that calculating confidence intervals at present can take a substantial amount of time.

## Arguments

- r_input
A formatted data frame using the

`format_mvmr`

function or an object of class`MRMVInput`

from`MendelianRandomization::mr_mvinput`

- pcor
A phenotypic correlation matrix including the correlation between each exposure included in the MVMR analysis.

- CI
Indicates whether 95 percent confidence intervals should be calculated using a non-parametric bootstrap.

- iterations
Specifies number of bootstrap iterations for calculating 95 percent confidence intervals.

## References

Sanderson, E., et al., An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings. International Journal of Epidemiology, 2019, 48, 3, 713-727. doi:10.1093/ije/dyy262