resquin 0.1.1

Changed the way the mahalanobis distance is calculcated in resp_distributions(), if missing values are allowed. Now within respondent mean imputation is used. Before missing values were turned to a value of 0, which is wrong in almost any case and would have skewed the results of respondents with missing values. Mean imputation is not an ideal solution, but it allows the observed data to influence the value of the mahalanobis distance value under missing data. Because within respondent mean imputation is not ideal, a new section in the description is added to call for caution when interpreting the mahalanobis distance values produced by resp_distributions() if min_valid_responses is smaller than 1.
Polished documentation (fixing typos etc.)
Added vignette on flagging respondents with flag_resp().
Added a disclaimer for handling of missing data in resp_nondifferentiation.
Added documentation on s3 methods.
Fixed bug in s3 print function which would crash if resp_styles() was used on even numbered response scales.
Added tests for functions added since 0.0.2.
Now depends on R version being >= to R version 4.1.
Added example data set nep from the GESIS panel.

resquin 0.1.0

Added resp_patterns() and resp_nondifferentiation() as a new function.
Added id column to all outputs to make it easier to identify respondents or merge function outputs to data frames. id is either True for an integer id, False for no id column, or a vector of unique integer or character values identifying each respondent.
Added flag_resp() function to quickly create and compare different flagging strategies based on response quality indicators.
Added s3 types to outputs of resp_*() and flag_resp() functions.
Added s3 print, summary and plot methods for outputs of resp_*() functions.
Added s3 summary method for flag_resp() output.

Changes in response to CRAN team. Changed license description in DESCRIPTION and removed License.md
Removed warning on development version at the start of the readme.md