Generalized Correlations and Initial Causal Path

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Documentation for package ‘generalCorr’ version 1.0.0

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abs_res Absolute residuals of kernel regression of x on y.
abs_stdapd Absolute values of gradients (apd's) of kernel regressions of x on y when both x and y are standardized.
abs_stdres Absolute values of residuals of kernel regressions of x on y when both x and y are standardized.
allPairs Report causal identification for all pairs of variables in a matrix.
badCol internal badCol
bigfp Compute the numerical integration by the trapezoidal rule.
cofactor Compute cofactor of a matrix based on row r and column c.
comp_portfo2 Compares two vectors (portfolios) using stochastic dominance of orders 1 to 4.
da internal da
da2Lag internal da2Lag
diff.e0 Internal diff.e0
dig Internal dig
e0 internal e0
EuroCrime European Crime Data
get0outliers Function to compute outliers and their count using Tukey method using 1.5 times interquartile range (IQR) to define boundarirs.
gmc0 internal gmc0
gmc1 internal gmc1
gmcmtx0 Compute the matrix R* of generalized correlation coefficients.
gmcmtxZ compute the matrix R* of generalized correlation coefficients.
gmcxy_np Function to compute generalized correlation coefficients r*x|y and r*(y|x).
goodCol internal goodCol
heurist Function to run a heuristic t test of the difference between two generalized correlations.
i internal i
ibad internal object
ii internal ii
j internal j
kern Function to run kernel regression with options for residuals and gradients.
min.e0 internal min.e0
minor Function to do compute the minor of a matrix defined by row r and column c.
mtx internal mtx
mtx0 internal mtx0
mtx2 internal mtx2
n internal n
nall internal nall
nam.badCol internal nam.badCol
nam.goodCol internal nam.goodCol
nam.mtx0 internal nam.mtx0
napair Function to do pairwise deletion of missing rows.
out1 internal out1
p1 internal p1
Panel2Lag Function to compute a vector of 2 lagged values of a variable from panel data.
PanelLag Function for computing a vector of one-lagged values of xj, a variable from panel data.
parcor_ijk Generalized partial correlation coefficient between Xi and Xj removing the effect of all other columns using the matrix R* of generalized correlation coefficients.
parcor_ridg Compute generalized (ridge-adjusted) partial correlation coefficients from matrix R*.
pcause Compute the bootstrap probability of correct determination of the causal direction.
prelec2 Intermediate weighting function giving Non-Expected Utility theory weights.
rhs.lag2 internal rhs.lag2
rhs1 internal rhs1
ridgek internal ridgek
rij internal rij
rijMrji internal rijMrji
rji internal rji
rrij internal rrij
rrji internal rrji
rstar Function to compute generalized correlation coefficients r*(x,y).
sales2Lag internal sales2Lag
salesLag internal salesLag
seed internal seed
sgn.e0 internal sgn.e0
some0Pairs Function reporting kernel causality results as a 7-column matrix where stochastic dominances orders are weighted by c(1.2,1.1, 1.05, 1) to compute an overall result for all orders of stochastic dominance.
somePairs Function reporting kernel causality results as a 7-column matrix.
sort.abse0 internal sort.abse0
sort.e0 internal sort.e0
sort_matrix Sort all columns of matrix x by j-th column while carrying along all columns.
stdz_xy Standardize x and y vectors to force zero mean and unit variance.
stochdom2 Compute vectors measuring stochastic dominance of four orders.
wtdpapb Creates input for the function stochdom2 for stochastic dominance.