Upgrade time-varying models using chunks and specifying prior parameters

[ntorresd]

• Please check if the PR fulfills these requirements

• I have read the CONTRIBUTING guidelines
• A new item has been added to NEWS.md
• Tests for the changes have been added (for bug fixes / features)
• Docs have been added / updated (for bug fixes / features)
• Checks have been run locally and pass

• What kind of change does this PR introduce? (Bug fix, feature, docs update, ...)
  This PR:

  • Upgrades the time-varying models to allow for force-of-infections estimations by chunks rather than year by year.
  • Updates testing strategy using chunks and data simulation
  • Partially solves Pass argument from fit_seromodel() to rstan::sampling() via ... #118

• What is the current behavior? (You can also link to an open issue here)

Currently, one value of the force-of-infection is estimated for every year in the time spanned by the serosurvey.

data(chagas2012)
serodata <- prepare_serodata(chagas2012)
seromodel <- fit_seromodel(serodata, foi_model = "tv_normal")

• What is the new behavior (if this is a feature change)?
  Now chunks can be specified either by size:

seromodel <- fit_seromodel(serodata, foi_model = "tv_normal", chunk_size = 10)

or explicitly specifying the chunk structure:

chunks <- rep(c(1, 2, 3, 4, 5), c(10, 10, 15, 15, max(serodata$age_mean_f)-50))
seromodel <- fit_seromodel(serodata, foi_model = "tv_normal", chunks = chunks)

• Does this PR introduce a breaking change? (What changes might users need to make in their application due to this PR?)
  Yes, two breaking changes are introduced in this PR:

1. The use of chunks is a breaking change allowing users to specify prior knowledge about the force-of-infection by assigning constant values of the force-of-infection to specific time intervals. The default behavior is chunk_size=1, which recovers previous results.
2. Now the user can specify the initial location and scale parameters of the distributions used in the stan files by means of foi_location and foi_scale parameters in fit_seromodel. The interpretation of these parameters may vary depending on the specified model. To recover previous results, users should use:

# tv_normal model
fit_seromodel(
   serodata = serodata,
   foi_model = "tv_normal",
   foi_location = 0,
   foi_scale = 1,
   ...
)

# tv_normal_log model
fit_seromodel(
   serodata = serodata,
   foi_model = "tv_normal",
   foi_location = -6,
   foi_scale = 4,
   ...
)

• Other information:

[ekamau]

looks good, except for the minor aesthetic in one of the stan files

[ekamau]

for uniformity remove the space between int and <lower=1>
i.e., int<lower=1> age_max;