It is therefore possible to incorporate simbiology in the process of development of models, sampling techniques and data collection. In addition, this function also allows users to perform experiments on data obtained from the model. A user can also use the functions from simbiology in MATLAB to generate bar charts and pie charts. The user may also write regular expressions and perform statistical analyses on data obtained from the model.
Data provided by the model can be viewed using the MetaBiology function in MATLAB. In addition, in order to adjust the parameters of the model, users can use MetaBiology in MATLAB. The user can select the parameter settings and then save them into MATLAB. After they are saved, the user can then adjust the parameters and compare the resulting model against the other models that have been used by other users.
The user can change the reference curve for all or a selected set of samples by using the utility function. The reference curve should be scaled according to the type of the parameter settings. This utility function in MATLAB enables the user to explore all the available options and then select the best one.
The data from the simulation can be combined with other sources in order to produce a more accurate output. The SimBiology function is used in order to combine data from other sources and then calculate the average or variance of the model.
One may use the SimBiology in MATLAB utility function to specify an estimation of the error in area estimation. This function also gives the error in area estimate in order to get an estimation of the model’s strength and measurement error. The functions enable the user to view the estimation as a probability density function.
The data from the simulation can be used to perform statistical tests in order to check if there are any anomalies in the data. These tests can be performed on the data collected from the user’s model. A user can also perform basic statistical tests using SimBiology in MATLAB.
The functions enable the user to select the different categories of data. The user can then perform an a priori test using the a priori function and the user can also perform a Bayesian analysis.
The a priori test can be performed on the simulated data obtained from the model. The SimBiology in MATLAB utility function helps the user to simulate data and then perform a Bayesian analysis.
The functionality of the simulation can be extended further by the usage of SimBiology in MATLAB. For example, data from the simulation can be integrated into a series of tests to be performed by another model to examine if there are any inconsistencies in the results of the original model.
The data from the simulation can be integrated into other models. The SimBiology utility function makes it possible to combine the simulated data from a number of models to perform a series of tests.
The Meta Biology utility function performs regression calculations using the results of the simulation. The regression calculation is based on the area estimate.