Run-time model status flags

[AlePalu]

Several optimizations can be turned on if we keep a run-time set of flags related to a model instance.
The idea would be to declare a public member struct runtime in ModelBase, and eventually enrich it as we move up in the model hierarchy. A model instance can then be queried at any point in the code for its run-time status.

A list of possible flags follow

flag	description
lambda_changed	tells whether a different value for the parameters' vector $\boldsymbol{\lambda}$ has been set. This can be easily detected in setters like set_lambda (and related more specific setters set_lambda_d and set_lambda_t), by checking if the given vector is equal to the currently stored one. If this is not the case, runtime.lambda_changed is set true.
R0_spec	can assume one between mass, identity, lumped to specify if the mass matrix $R_0$ should be returned as the full mass matrix, the identity matrix or the lumped mass matrix respectively. Supplied by the user.
weight_changed	tells, in WLS problems, or algorithms related to them, whether a different weight matrix $W$ has been supplied. Detectable from setter.
obs_changed	tells whether a different observation vector $\boldsymbol{y}$ has been set. Detectable from setter.
is_parallel	tells whether multithreading support is enabled. If so, algorithms for which a parallel implementation is available should be executed in their parallel version.
has_nan	tells wheter there are some missing entries in the observation vector. Currently this is provided by the has_nan() method, would be better to keep this information centralized. Detectable from set_data()

Checks could eventually rely on fast hash functions, which work on large chunks of data (avoiding possible expensive loops over large matrices/vectors).
Model implementations must then exploit the knowledge on the runtime configuration to eventually bypass computations, whenever this is possible.