TAM — TAM-utilities" />
TAM-utilities.RdUtility functions in TAM.
## RISE item fit statistic of two models IRT.RISE( mod_p, mod_np, use_probs=TRUE ) ## model-implied means tam_model_implied_means(mod) ## information about used package version tam_packageinfo(pack) ## call statement in a string format tam_print_call(CALL) ## information about R session tam_rsessinfo() ## grep list of arguments for a specific variable tam_args_CALL_search(args_CALL, variable, default_value) ## requireNamespace with message of needed installation require_namespace_msg(pkg) ## add leading zeroes add.lead(x, width=max(nchar(x))) ## round some columns in a data frame tam_round_data_frame(obji, from=1, to=ncol(obji), digits=3, rownames_null=FALSE) ## round some columns in a data frame and print this data frame tam_round_data_frame_print(obji, from=1, to=ncol(obji), digits=3, rownames_null=FALSE) ## copy of CDM::osink tam_osink(file, suffix=".Rout") ## copy of CDM::csink tam_csink(file) ## base::matrix function with argument value byrow=TRUE tam_matrix2(x, nrow=NULL, ncol=NULL) ## more efficient base::outer functions for operations "*", "+" and "-" tam_outer(x, y, op="*") ## row normalization of a matrix tam_normalize_matrix_rows(x) ## row normalization of a vector tam_normalize_vector(x) ## aggregate function for mean and sum based on base::rowsum tam_aggregate(x, group, mean=FALSE, na.rm=TRUE) ## column index when a value in a matrix is exceeded (used in TAM::tam.pv) tam_interval_index(matr, rn) ## cumulative sum of row entries in a matrix tam_rowCumsums(matr) ## extension of mvtnorm::dmvnorm to matrix entries of mean tam_dmvnorm(x, mean, sigma, log=FALSE ) ## Bayesian bootstrap in TAM (used in tam.pv.mcmc) tam_bayesian_bootstrap(N, sample_integers=FALSE, do_boot=TRUE) ## weighted covariance matrix tam_cov_wt(x, wt=NULL, method="ML") ## weighted correlation matrix tam_cor_wt(x, wt=NULL, method="ML") ## generalized inverse tam_ginv(x, eps=.05) ## generalized inverse with scaled matrix using MASS::ginv tam_ginv_scaled(x, use_MASS=TRUE) ## remove items or persons with complete missing entries tam_remove_missings( dat, items, elim_items=TRUE, elim_persons=TRUE ) ## compute AXsi given A and xsi tam_AXsi_compute(A, xsi) ## fit xsi given A and AXsi tam_AXsi_fit(A, AXsi) ## maximum absolute difference between objects tam_max_abs( list1, list2, label ) tam_max_abs_list( list1, list2) ## trimming increments in iterations tam_trim_increment(increment, max.increment, trim_increment="cut", trim_incr_factor=2, eps=1E-10, avoid_na=FALSE) ## numerical differentiation by central difference tam_difference_quotient(d0, d0p, d0m, h) ## assign elements of a list in an environment tam_assign_list_elements(x, envir)
| mod_p | Fitted model |
|---|---|
| mod_np | Fitted model |
| mod | Fitted model |
| use_probs | Logical |
| pack | An R package |
| CALL | An R call |
| args_CALL | Arguments obtained from |
| variable | Name of a variable |
| default_value | Default value of a variable |
| pkg | String |
| x | Vector or matrix or list |
| width | Number of zeroes before decimal |
| obji | Data frame or vector |
| from | Integer |
| to | Integer |
| digits | Integer |
| rownames_null | Logical |
| file | File name |
| suffix | Suffix for file name of summary output |
| nrow | Number of rows |
| ncol | Number of columns |
| y | Vector |
| op | |
| group | Vector of grouping identifiers |
| mean | Logical indicating whether mean should be calculated or the sum or vector or matrix |
| na.rm | Logical indicating whether missing values should be removed |
| matr | Matrix |
| sigma | Matrix |
| log | Logical |
| N | Integer |
| sample_integers | Logical indicating whether weights for complete cases should be sampled in bootstrap |
| do_boot | Logical |
| wt | Optional vector containing weights |
| method | Method, see |
| rn | Vector |
| dat | Data frame |
| items | Vector |
| elim_items | Logical |
| elim_persons | Logical |
| A | Array |
| xsi | Vector |
| AXsi | Matrix |
| increment | Vector |
| max.increment | Numeric |
| trim_increment | One of the methods |
| trim_incr_factor | Factor of trimming in method |
| eps | Small number preventing from division by zero |
| use_MASS | Logical indicating whether MASS package should be used. |
| avoid_na | Logical indicating whether missing values should be set to zero. |
| d0 | Vector |
| d0p | Vector |
| d0m | Vector |
| h | Vector |
| envir | Environment variable |
| list1 | List |
| list2 | List |
| label | Element of a list |