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dnn 0.0.8

Cox fitting now handles tied observed times with Breslow risk sets in R and C++. Baseline hazards, survival curves, residuals, and RMST use consistent grouped risk sets. Full-batch fitting caches tie groups.
Corrected native tanh and Cox gradients, weighted MSE, binomial, Poisson, and MAE loss calculations, Adam learning-rate scaling, and optimizer-state initialization. Native fitting preserves the supplied model.
Observation weights default to 1 and accept finite nonnegative vectors of sample size, including one-column matrices converted to vectors. Weights are not normalized. Cox sample weights remain unsupported.
Corrected survival formula handling, single-layer and narrow-network dimensions, censored-maximum handling, and deepAFT convergence updates.
Corrected survival residuals, exact integration of stepwise model-based RMST, IBS ordering, small-sample IPCW grouping, and uncensored imputation.
Tuning rebuilds sampled architectures, returns the best model with its matching controls, bounds failed attempts, and errors when no candidate is selected. Iteration and fold counts are validated before training.
Rcpp fitting disables unsupported dropout with a warning. Final dnnFit diagnostics are evaluated on all observations with dropout disabled.
Non-finite numerical results now produce an explicit error recommending rescaling the data or adjusting model parameters.
Added regression tests for the corrected loss functions, fitting paths, survival calculations, tuning, and input contracts.

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