View source: R/translogMonoRestr.R
| translogMonoRestr | R Documentation | 
Create matrix to check or impose the monotonicity restrictions of a translog function.
translogMonoRestr( xNames, data, dataLogged = FALSE, box = FALSE )
| xNames | a vector of strings containing the names of the independent variables. | 
| data | dataframe containing the data. | 
| dataLogged | logical. Are the values in  | 
| box | logical. Should monotonicity be imposed within 
an n-dimensional box that includes all points in  | 
translogMonoRestr returns a matrix of dimension
( n \cdot N ) \times c,
where n is the number of independent varables,
N is the number of data points at which monotonicity
should be imposed (if argument box is FALSE,
N is the number of rows in data;
if argument box is TRUE, N = 2^n),
and c = 1 + n ( n + 3 ) / 2 is the number of (linearly independent) 
coefficients.
Multiplying a row of this matrix (e.g.\ the kth row of M)
by the vector of coefficients (β)
results in the derivative of the dependent variable (y) 
with respect to one independent variable (e.g.\ x_i)
at one data point (e.g.\ j): 
M[k,] * β = ( d log y )/( d log x_i )
, evaluated at x_{1j}, ..., x_{nj}, where k = ( i - 1 ) N + j. Hence, the observations run faster than the independent variables.
Arne Henningsen
translogEst, translogDeriv,
and translogCheckMono
   data( germanFarms )
   # quantity of variable inputs
   germanFarms$qVarInput <- germanFarms$vVarInput / germanFarms$pVarInput
   # matrix to check or impose monotonicity at all observations
   monoRestrObs <- translogMonoRestr( c( "qLabor", "land", "qVarInput" ),
      germanFarms )
   # matrix to check or impose monotonicity within a box that includes all 
   # observations
   monoRestrBox <- translogMonoRestr( c( "qLabor", "land", "qVarInput" ),
      germanFarms, box = TRUE )
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