emhawkes 1.0.0

Initialization and estimation

• Default simulation, likelihood and fitting to lambda_component0 = "auto" (NULL is an alias). Report whether mean or zero intensity components were selected. Mean initialization applies to supported stable constant linear models, including mapped kernels; other models use zero and recommend an explicit initial state. Components exclude the baseline intensity.
• Correct the univariate half-mean initialization. Preserve explicit initial states, hold the selected fitting rule fixed and differentiate mean components. Store the rule and actual components in fit diagnostics; recover the actual initial states when replaying older saved fits. Automatic initialization can change simulated paths and fitted estimates relative to previous releases.
• Add hfit(optimizer = "stats"), using R’s optim() or constrOptim() without maxLik. Support fixed/shared parameters, derivatives, linear inequalities and box bounds, with separate result methods and fitted-model reconstruction. Make maxLik optional while retaining it as the default provider; install it explicitly when using the default. Keep numerical score steps within linear constraints and reject unsupported controls and equality constraints.
• Accept both constraint and constraints, preserving positional arguments. Reject simultaneous non-NULL values and normalize either spelling for maxLik.
• Add fitted_hspec(), fit_initial_state() and fit_diagnostics() to restore fitted specifications and inspect optimizer, engine and curvature choices.
• Add final_hessian = "stable", with scaled differences, analytic-score differentiation where available and step-stability checks. Withhold Wald covariance when curvature or constraint checks fail. Stable curvature is optional for maxLik and the default for stats fits; it does not establish finite-sample confidence-interval coverage.

Computation

• Add registered Rcpp likelihood and intensity/residual inference engines for supported numeric, parameter-only and observed-state specifications. Preserve callback defaults and event timing; unsupported models retain R evaluation. emhawkes.engine selects automatic, reference R or required C++ likelihoods. Source installation now requires Rcpp and a C++ compiler.
• Add opt-in analytic scores for numeric models and supported component functions through gradient = "analytic" and jacobian. Preserve shared/fixed parameters and initial-state derivatives; reduce observed-baseline Jacobian storage. Numerical optimizer differentiation remains the default.
• Add a complete native simulation event loop for supported numeric and callback specifications, including multivariate and mapped multi-kernel models. Reduce history copying and reuse equal decay factors within each row. Preserve R fallback, explicit initial states, callback behavior and random-draw order when comparing the engines. The likelihood engine option does not select the simulation path.
• Preserve native RNG state around callback and warning handlers, including errors, nested simulation and handlers that draw random numbers. Add checks for older R/Rcpp versions, garbage collection, interruption and memory access.

Corrections and diagnostics

• Register S4 initialization and display methods through the package namespace. Preserve construction and saved-fit restoration in sessions where methods is installed but not attached, including isolated stats-optimizer sessions.
• Validate observations, initial components, decay rates, mappings, counting processes and callback parameters consistently. Correct multi-kernel event types, univariate multi-kernel likelihoods and constant-model stability checks. Preserve admissible signed components and stop when no further event occurs.
• Correct event-side baseline recording and return empty residuals for event types with fewer than two events. Use stable exponential integrals and log-scale residual distributions. Correct trapezoid-exponential generation and add log/tail distribution options. Paths can change where event selection or random generation was corrected.
• Correct expected_tau() for widely separated time scales and a positive probability of no further event. Correct mark handling in hvol() and reject models outside the bivariate moment formula’s scope.
• Preserve display options when printing paths, honor zero displayed rows and retain single-row matrix formatting. Make initialization, callback, dimension, early-stopping and unavailable-curvature messages actionable.

emhawkes 0.9.8

Fixed some bugs

Breaking changes

• Flexible residual point process with self/mutually exciting and exponential decay model is available.

emhawkes 0.9.7

Fixed some bugs, improved efficiency in this version and several features have been added.

Breaking changes

• The lambda0 argument name used in previous versions has been changed to lambda_component0 in this version. This is to clearly indicate the meaning of the argument and to avoid confusion.

• The name of method vol is changed to hvol and this feature is currently experimental.

• The Vignette file contains more examples and explanations.

emhawkes 0.9.6

Fixed some bugs, improved efficiency in this version and several features have been added.

Breaking changes

• Slot eta is introduced which represents the constant part of impact.

• The concepts of rambda and rambda_component are introduced. They are closely related to the right-continuous version of the intensity process.

• For inference of intensity and goodness of fit, infer_lambda and residual_process functions are implemented.

• The method vol to measure the volatility is introduced and this feature is currently experimental.