JumpOverCoef: Proposing coefficients for the Jump Pver MCMC move.
In gpapadog/LERCA: Local Exposure-Response Confounding Adjustment

The Jump Over move is accompanied with proposing new slopes that ensure a continuous ER.

1
2
3

JumpOverCoef(current_coefs, prop_cuts, cuts, curr_exper_same,
  prop_exper_same, curr_exper_comb, prop_exper_comb, curr_exper_split,
  prop_exper_split, jump_slope_tune)

`current_coefs`	The current coefficients of the MCMC. Three dimensional array with dimensions corresponding to exposure/outcome model, experiment, and coefficients (intercept, slope, covariates).
`prop_cuts`	Numeric vector with the K locations of the proposed experiment configuration.
`cuts`	Numeric vector with the K locations of the current experiment configuration.
`curr_exper_same`	Numeric vector. Indices of experiments in the current experiment configuration that did not get combined or split. They should be in the same order as prop_exper_same.
`prop_exper_same`	Numeric vector with the indices of the experiments in the proposed experiment configuration that did not get combined or split.
`curr_exper_comb`	Numeric vector of length two with entries the indices of the experiments with respect to the current experiment configuration that were proposed to be combined.
`prop_exper_comb`	Numeric. Index of the experiment in the proposed experiment configuration corresponding to the combined experiment.
`curr_exper_split`	Numeric. Index of the experiment in the current experiment configuration that is proposed to be split.
`prop_exper_split`	Numeric vector of length two. Indices of the experiments in the proposed experiment configuration that are the result of a split in an experiment.
`jump_slope_tune`	Numeric. The standard deviation of the proposal on slopes for the two experiments in the proposed experiment configuration that are the result of an experiment's split.