Package: gjam 2.7

overview | model summary | data types | effort and weight of discrete data | using gjam | simulated data | my data | sensitivity to predictors | plotting output | flexibility in gjam | heterogeneous effort | specifying censored intervals | prior distribution on coefficients | species-factor levels that do not occur | sample effort in count data | sample effort in composition data | the partition in ordinal data | categorical data | combinations of data types | random effects | missing data, out-of-sample prediction | prediction with heterogenous effort | conditional prediction | conditional parameters | presence-only data with effort | dimension reduction | big-S composition data: fungal endophytes | interactions and indirect effects | joint trait modeling | trait response model (TRM) | input data | traits by species | factors in this example | TRM analysis | interactions and indirect effects | predictive trait model (PTM) | start with species abundance | trouble shooting in PTM | selecting variables | trouble shooting | reference notes | more on parameter dimensions | more on factors in $\mathbf{X}$ | algorithm summary | acknowledgements | references