Package changes from previous lphom version 0.3.5-4

Compared to version 0.3.5-4 of lphom, the new version:

• solves a bug in the adjust2integers() function. In the previous version, instead of applying the solver argument declared in the function, it incorrectly used the solver argument declared when creating the x object. It has also bounded the computational time required with argument solver = "lp_solve" when performing integer linear programming. Now lphom requires package lpSolve (>= 5.6.18).
• solves a bug in the plot.lphom() method. In the previous version, it produced an error when trying to plot an object generated with _dual functions.
• reviews documentation and updates references.

Package changes from previous lphom version 0.3.1-1

Compared to version 0.3.1-1 of lphom, the new version:

• includes two new arguments (apriori and lambda) in functions lphom(), tslphom(), nslphom() and lclphom(). The apriori argument allows to introduce in the inference process information from polls or some other a priori knowledge/intuition about the row standardized transfer probabilities. The lambda argument controls the weight the user assigns to the a priori information.
• offers an implementation of the bottom-up approach for ecological inference through the rslphom() function.
• expands the number of scenarios in terms of how entries of new voters and exits of previous voters are handled by the different functions. The new options include: "ordinary", "enriched", "semifull", "fullreverse", "adjust1" and "adjust2".
• modifies the lclphom() algorithm by including the two possibilities of calculating the distance with the global matrix. The distance with the global matrix that is used to generate the local solution and the distance with the global matrix where the local solution integrates into. This is controlled with the type.errors argument.
• incorporates to the outputs of the functions lphom(), tslphom(), nslphom(), lclphom(), rslphom(), lphom_joint(), tslphom_joint() and nslphom_joint() the list deterministic.bounds. The object deterministic.bounds contains both the deterministic global and unit bounds that derive from the observed margins.
• reviews documentation and updates references.