install.packages('nmm')add_variable adds columns to the data matrixMNlogitf or MNdogitf returns log-likelihood(LL) expression for discrete equations of "logit" or "dogit" model.LL_joint_no_corr Function for log-likelihood without correlation between
continuous and discrete equationsLL_joint Function for joint log-likelihood with correlation between
continuous and discrete equationscheck_par_av Checks if all elements of par are available in object.combine_attr_deriv combines attributes of two deriv() results.get_start_disc get starting values for discrete choice model.grad_hess_eval forms function of gradient and Hessian of log-likelihood produced
by f_create.formula2string removes square brackets from the supplied expressions.
Convert par[2] -> par2, sigma[2] -> sigma_2_, sigma[2,3] -> sigma_2x2convert_attr2exp converts symbolic attribute of derivative into expression object.get_npar Get number of parameters or vector of parameters in supplied equations.
Extracts the number of parameters used in equations. Parameters are given as par[1], ..., par[n].in2nmm convert some estimation results into nmm object.get_par replaces names of parameters with par[i].f_create creates functions for log-likelihood of different models.get_start_cont get starting values for continuous equations.get_start get starting values for discrete or continuous choice model.mlsem returns expression of log-likelihood for joint normal distribution,
for maximum likelihood (ML), Simultaneous Equations Models (SEM) variant.nrParam return number of parameters used in the estimation.replace_par replaces text with other text.wxMaxima does symbolic computation in 'Maxima'
Requires installation of Maxima software.cond_expr returns moments of conditional multivariate normal distribution X|Y (last
variable is dependent). Only expression for X|Y. Requires installation of Maxima software.extract_attr_deriv converts attributes(hessian/gradient) of deriv() into a
matrix of character strings.maxle returns expression of log-likelihood (LL) of joint normal distribution.cond_mean_cov_expr returns conditional mean and variance X|Y of conditional multivariate
normal distribution . X is discrete variable, Y are continuous variables.
No correlation between discrete eq.replace_par_wrap replace text with other text, wrapper of replace_par.maxle_p returns expression of partitioned log-likelihood.
f(y1,y2,..,yn)=f(y1)f(y2|y1)f(y3|y2y1)...f(yn|y1..y(n-1))prepare_data prepare data for the estimation.string2formula add square brackets to expressions.
Reverse of formula2string. Convert par[2] <- par2, sigma[2] <- sigma_2_, sigma[2,3] <- sigma_2x2