                 Changes in version 2.1.5 (2026-07-18)                  

Minor Changes

  - The output from the gof_rem() function is now an dream_gof S3
    object. The following methods are included for this object class:
    plot(), summary(), and print().
  - Added a new relational event sequence data.frame object to help
    users get started with one-mode relational event analysis. The new
    object is named simulated.res.
  - Happy dreaming!

                 Changes in version 2.1.4 (2026-06-29)                  

Minor Changes

  - Set a default value for the plot() S3 method for dream_rem objects,
    so that the user does not have to initially specify a value.
  - Updated the predict() S3 method for dream_rem objects to now allow
    updated dream_sequence objects to based the predicted event rates
    on.
  - Updated the print() and summary() S3 methods for dream_sequence
    objects to relay additional information about the processed
    relational event sequence to the user.
  - Fixed a small bug in the simulate_rem_seq() function for the
    three-cycles statistic when parallel processing is requested.

                 Changes in version 2.1.3 (2026-06-11)                  

Minor Changes

  - Fixed a bug in the gof_rem() function that resulted in the
    proportion of receivers correctly predicted to be incorrect, and
    added the rseed argument to allow the user to set the random seed.
  - Add the cumulative option to the create_res() function as an
    additional option. Case-control sampling is now indicated by the
    argument case_control in the create_res() function.

                 Changes in version 2.1.2 (2026-06-03)                  

Minor Changes

  - Added three new functions for the examination of relational event
    model fits. First, gof_rem() computes the proportion of correctly
    predicted dyadic events for a dream_rem relational event model fit.
    Secondly, we added the plot() and residuals() S3 methods for the
    dream_rem object class. Please see the function documentation pages
    for more information on these new functions. Happy dreaming!

                 Changes in version 2.1.1 (2026-05-29)                  

Major Changes

  - The package has undergone a new API for the analysis of relational
    event sequences aimed at reducing redundant user-inputs and
    increasing useability. Importantly, the package now contains two S3
    object classes: dream_sequence and dream_rem, where dream_sequence
    is the object class created after using create_res() in the dream
    package to generate the post-processing relational event sequence
    (i.e., (sampled) realized events and sampled control/null events) or
    after using dream_sequence(), a new function to create the S3 object
    based upon a user-generated processing sequence. Moreover, in prior
    versions of the package, users had to input 6 arguments into the
    functions to compute various sufficient network statistics (e.g.,
    four-cycles, repetition), these 6 arguments are now pulled from the
    dream_sequence data object. Additionally, the functions that compute
    the sufficient network statistics add the vector of computed
    statistics to the user-inputted dream_sequence object as an
    additional element in the statistics list. The estimate_rem()
    function now relies upon the user-created dream_sequence objects and
    extracts the relational event model covariates from the data object.
    Finally, dream_rem S3 objects now contain a new set of functions to
    extract relevant model information: vcov(), logLik(), coef(), and
    predict().
  - create_riskset_dynamic() and create_riskset_constant() have been
    replaced
    by the new function create_res(), which internally is the same as
    the aforementioned functions and generate risksets based upon the
    riskset argument. We encourage users to read the help page for the
    create_res() to see the updated set of full riskset possibilities.
  - As mentioned above, the dreamstats_ series of functions have been
    updated to reduce the number of arguments supplied by the user.
    Previously, the following arguments needed to be specified: time,
    sender, receiver, eventID, observed, and sampled. However, the new
    updated functions internally create these based upon the data
    argument which is an S3 dream_sequence object.
  - The newly created S3 dream_sequence object, which is created using
    the create_res() function, also has a function named
    dream_sequence() that can create a dream_sequence object based upon
    the user-inputted values. In addition, the as.data.frame() has been
    supplied to extract the post-processing relational event sequence
    and the computed statistics. Users may find this function useful if
    they would like to estimate the relational event model by a
    different modeling function such as the clogit() function in the
    survival package or a user-created function.
  - The new package version also includes a new suite of functions that
    expands the set of exogenous statistics for the estimation of
    relational event models. These are dreamstats_actor(),
    dreamstats_actorfe(), dreamstats_dyadic(), dreamstats_dyadfe(), and
    dreamstats_event(). These functions, respectively, allow users to
    (1) add actor-level time-varying and time-invariant exogenous
    covariates, (2) add actor-level (sender and receiver) fixed effects,
    (3) add dyadic-level time-varying and time-invariant exogenous
    covariates, (4) add dyadic-level fixed effects, and (3) add
    event-level exogenous covariates.
  - Lastly, the estimate_rem() function now allows for the estimation of
    interval timing relational event models. In terms of estimation
    routines, the c++ functions to compute the model log-likelihoods,
    hessians, and gradients are now computed using RcppArmadillo with
    the arma set of functions.
  - All functions that were deprecated in dream 1.1.1 were removed, in
    addition to the past function arguments for the dreamstats_
    functions.

                 Changes in version 1.1.1 (2026-03-25)                  

Major Changes

  - All remstats_-related functions were renamed to dreamstats_ to
    provide a more consistently named API for the dream package. As a
    result, all remstats_ original functions are now deprecated starting
    on version 1.1.1, but remain available in this update.
  - create_riskset() was renamed to create_riskset_constant().
  - All functions that were deprecated in dream 1.0.0 were removed.

                 Changes in version 1.0.1 (2026-02-07)                  

Major Changes

  - Implemented a new function to create time-dynamic risk sets for one-
    and two-mode relational event sequences. The new function is named
    create_riskset_dynamic().

Minor Changes

  - Updated the remstats_-related C++ files to delete past network edges
    (i.e., past event weights) that are smaller than the past event cut
    off value (i.e., dyadic_weight) when this feature is selected by the
    user. That is, when the dyadic_weight argument is non-zero.

                 Changes in version 1.0.0 (2026-01-20)                  

Major Changes

  - Added a NEWS.md file to track changes to the package.
  - Two key changes occured in the new version of dream package. First,
    the majority of functions now depend upon c++ routines via the Rccp
    package to improve computational runtime. For instance, the new
    function to compute the repetition network statistic,
    remstats_repetition(), is around 90 times faster than the previous
    function, computeRepetition(), in dream version 0.0.1. Secondly, the
    dream package has an updated API to allow better categorization for
    the functions. Please run ?dream for more details on the new API.
    Based upon this transition, the original functions are now
    deprecated starting on version 1.0.0, but remain available in this
    update.
  - The following functions were deprecated for remstats_triads():
    computeISP(), computeITP(), computeOSP(), computeTriads, and
    computeOTP().
  - The following functions were deprecated for remstats_degree():
    computeSenderOutdegree(), computeReceiverOutdegree(),
    computeSenderIndegree(), and computeReceiverIndegree().
  - estimateREM() was deprecated for estimate_rem_logit().
  - simulateREseq() was deprecated for simulate_rem_seq().
  - computeFourCycles() was deprecated for remstats_fourcycles().
  - computeRemDyadCut() was deprecated for remstats_dyadcut().
  - computePersistence() was deprecated for remstats_persistence().
  - computePersistence() was deprecated for remstats_persistence().
  - processOMEventSeq() and processTMEventSeq() were deprecated for
    createriskset().
  - computePrefAttach() was deprecated for remstats_prefattachment().
  - computeRepetition() was deprecated for remstats_repetition().
  - computeRepetition() was deprecated for remstats_repetition().
  - remExpWeights() was deprecated and will not be replaced in the
    current version as the updated functions do not require it.
  - remExpWeights() was deprecated and will not be replaced in the
    current version as the updated functions do not require it.
  - computeTMDegree() was deprecated for netstats_tm_degreecent().
  - computeTMEgoDis() was deprecated for netstats_tm_egodistance().
  - computeBCConstraint() was deprecated for netstats_tm_constraint().
  - computeBCES() was deprecated for netstats_tm_effective().
  - computeBCRedund() was deprecated for netstats_tm_redundancy().
  - computeBurtsConstraint() was deprecated for
    netstats_om_constraint().
  - computeBurtsES() was deprecated for netstats_om_effective().
  - computeHomFourCycles() was deprecated for
    netstats_tm_homfourcycles().
  - computeLealBrokerage() was deprecated for netstats_om_pib().
  - computeNPaths() was deprecated for netstats_om_nwalks().
  - computeTMDens() was deprecated for netstats_tm_density().
