LMMsolver 1.0.7
- Improved efficiency for models where the
residual
argument of LMMsolve()
is used.
- A data.frame
trace
with convergence sequence for log-likelihood and effective dimensions, added as extra output returned by LMMsolve()
.
- Bug in v1.0.6 for GLMM models fixed.
- Coefficients for three way interactions with one factor and two non-factors are now labelled correctly.
- Standard errors in function
obtainSmoothTrend()
for GLMM models are now calculated.
LMMsolver 1.0.6
- A new argument
grpTheta
for LMMsolve()
to give components in the model the same penalty.
- The dependency package
sp
is replaced by sf
.
- A small bug for models with more than 10.000 observations and only a numeric variable in the random part of the model is fixed.
- Weights are now checked for missing values after removing observations with missing values in response. This prevents spurious errors when both response and weight are missing.
LMMsolver 1.0.5
- Small bugs in assignment of names to fixed model coefficients when columns were dropped from the model are fixed.
- Calculation of standard errors for coefficients, with
coef(obj, se = TRUE)
.
- Implementation of Generalized Linear Mixed Models (GLMM) with additional argument
family
in LMMsolve
function.
- Variance components and splines can be conditional on a factor. For variance components, this is implemented in the
cf(var, cond, level)
function. For 1D and 2D splines, additional arguments cond
and level
are added.
- Several small bugs fixed.
LMMsolver 1.0.4
- Improved computation time for calculation of standard errors. Implementation in C++ and using the ‘sparse inverse’.
- Row-wise Kronecker product for
spam
matrices implemented in C++. Important for tensor product P-splines with improved computation time and memory allocation.
LMMsolver 1.0.3
- Improved computation time and memory allocation, especially important for big data with many observations (the number of rows in the data frame).
- Replaced the default
model.matrix
function by Matrix::sparse.model.matrix
to generate sparse design matrices.
- In function
obtainSmoothTrend
the standard errors are only calculated if includeIntercept = TRUE
.
- Several small bugs fixed.
LMMsolver 1.0.2
- First and second order derivatives are now calculated correctly.
- Several small bugs fixed.
- Updated tests to pass checks on macM1.
LMMsolver 1.0.1
weights
argument in LMMsolve function added
- Function
obtainSmoothTrend
returns in addition to the predictions the standard errors.
- Generalized Additive Model (GAM) added for one-dimensional splines, i.e. more
spl1D()
components can be added to the spline
argument of LMMsolve function
- Improved efficiency of calculating the sparse inverse using super-nodes.
- Replaced the original P-splines penalty
D'D
with a scaled version which is far more stable if there are many knots.
- Several bugs fixed.
LMMsolver 1.0.0