LeastSquaresResults object
Package: SimBiology.fit
Results object containing estimation results from least-squares regression
Description
The LeastSquaresResults
object is a superclass of two results
objects: NLINResults object
and OptimResults object
. These objects contain estimation results from
fitting a SimBiology® model to data using sbiofit
with any supported algorithm.
If sbiofit
uses the nlinfit
estimation
algorithm, the results object is the NLINResults
object. If
sbiofit
uses any other supporting algorithm, then the results
object is an OptimResults
object. See the sbiofit
function for the list of supported algorithms.
Method Summary
boxplot | Create box plot showing the variation of estimated SimBiology model parameters |
fitted | Return simulation results of SimBiology model fitted using least-squares regression |
plot | Compare simulation results to the training data, creating a time-course subplot for each group |
plotActualVersusPredicted | Compare predictions to actual data, creating a subplot for each response |
plotResidualDistribution | Plot the distribution of the residuals |
plotResiduals | Plot residuals for each response, using time, group, or prediction as x-axis |
predict | Simulate and evaluate fitted SimBiology model |
random | Simulate SimBiology model, adding variations by sampling error model |
summary | Return structure array that contains estimated values and fit quality statistics |
Properties
GroupName | Categorical variable representing the name of the group associated
with the results, or [] if the
'Pooled' name-value pair argument was set to
true when you ran
sbiofit . |
Beta | Table of estimated parameters where the jth row
represents the jth estimated parameter
βj. It contains
transformed values of parameter estimates if any parameter transform is
specified. Standard errors of these parameter estimates
( It can also contain the following variables:
|
ParameterEstimates | Table of estimated parameters where the jth row
represents the jth estimated parameter
βj. This table
contains untransformed values of parameter estimates. Standard
errors of these parameter estimates
( It can also contain the following variables:
|
J | Jacobian matrix of the model, with respect to an estimated parameter,
that is,
where ti is the ith time point, βj is the jth estimated parameter in the transformed space, and yk is the kth response in the group of data. |
COVB | Estimated covariance matrix for Beta , which is
calculated as: COVB = inv(J'*J)*MSE . |
CovarianceMatrix | Estimated covariance matrix for
ParameterEstimates , which is calculated as:
CovarianceMatrix = T'*COVB*T , where T =
diag(JInvT(Beta)) .
For instance, suppose you
specified the log-transform for an estimated parameter
|
R | Residuals matrix where Rij is the residual for the ith time point and the jth response in the group of data. |
LogLikelihood | Maximized loglikelihood for the fitted model. |
AIC | Akaike Information Criterion (AIC), calculated as AIC =
2*(-LogLikelihood + P) , where P is the
number of parameters. |
BIC | Bayes Information Criterion (BIC), calculated as BIC =
-2*LogLikelihood + P*log(N) , where N is
the number of observations, and P is the number of
parameters. |
DFE | Degrees of freedom for error, calculated as DFE =
N-P , where N is the number of
observations and P is the number of
parameters. |
MSE | Mean squared error. |
SSE | Sum of squared (weighted) errors or residuals. |
Weights | Matrix of weights with one column per response and one row per observation. |
EstimatedParameterNames | Cell array of character vectors specifying estimated parameter names. |
ErrorModelInfo | Table describing the error models and estimated error model
parameters.
There are four built-in error models. Each model defines the error using a standard mean-zero and unit-variance (Gaussian) variable e, the function value f, and one or two parameters a and b. In SimBiology, the function f represents simulation results from a SimBiology model.
|
EstimationFunction | Name of the estimation function. |
DependentFiles | File names to include for deployment. |
Note
Loglikelihood
, AIC
, and
BIC
properties are empty for
LeastSquaresResults
objects that were obtained before
R2016a.
Version History
See Also
NLINResults object
| OptimResults object
| sbiofit
| sbiofitmixed