Generalized Correlations and Initial Causal Path


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Documentation for package ‘generalCorr’ version 1.1.0

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generalCorrInfo-package generalCorr package description:
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_stdapdC Absolute values of gradients (apd's) of kernel regressions of x on y when both x and y are standardized and control variables are present.
abs_stdres Absolute values of residuals of kernel regressions of x on y when both x and y are standardized.
abs_stdresC Absolute values of residuals of kernel regressions of x on y when both x and y are standardized and control variables are present.
abs_stdrhserC Absolute residuals kernel regressions of standardized x on y and control variables, Cr1 has abs(RHS*y)
abs_stdrhserr Absolute values of Hausman-Wu null in 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.
bootPairs Compute matrix of n999 rows and p-1 columns of bootstrap 'sum' (strength from Cr1 to Cr3).
causeSummary Kernel causality summary of evidence for causal paths from three criteria
causeSummary0 Older Kernel causality summary of evidence for causal paths from three criteria
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
generalCorrInfo generalCorr package description:
get0outliers Function to compute outliers and their count using Tukey method using 1.5 times interquartile range (IQR) to define boundaries.
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 Heuristic t test of the difference between two generalized correlations.
i internal i
ibad internal object
ii internal ii
j internal j
kern Kernel regression with options for residuals and gradients.
kern_ctrl Kernel regression with control variables and optional residuals and gradients.
mag Approximate overall magnitudes of kernel regression partials dx/dy and dy/dx.
mag_ctrl After removing control variables, magnitude of effect of x on y, and of y on x.
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.
naTriplet Function to do matched deletion of missing rows from x, y and control variable(s).
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.
parcorMany Report many generalized partial correlation coefficients allowing control variables.
parcor_ijk Generalized partial correlation coefficients between Xi and Xj after removing the effect of xk.
parcor_linear Partial correlation coefficient between Xi and Xj after removing the linear effect of all others.
pcause Compute the bootstrap probability of correct 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
silentMtx No-print kernel-causality unanimity score matrix with optional control variables
silentMtx0 Older kernel-causality unanimity score matrix with optional control variables
silentPairs No-print kernel causality scores with control variables Hausman-Wu Criterion 1
silentPairs0 Older version, kernel causality weighted sum allowing control variables
some0Pairs Function reporting kernel causality results as a detailed 7-column matrix
someCPairs Kernel causality computations admitting control variables reporting a 7-column matrix (has older Cr1)
someCPairs2 Kernel causality computations admitting control variables reporting a 7-column matrix, ver. 2
someMagPairs Summary magnitudes after removing control variables in several pairs where dependent variable is fixed.
somePairs Function reporting kernel causality results as a 7-column matrix.
somePairs2 Function reporting kernel causality results as a 7-column matrix, version 2.
sort.abse0 internal sort.abse0
sort.e0 internal sort.e0
sort_matrix Sort all columns of matrix x with respect to the j-th column.
stdres Residuals of kernel regressions of x on y when both x and y are standardized.
stdz_xy Standardize x and y vectors to achieve zero mean and unit variance.
stochdom2 Compute vectors measuring stochastic dominance of four orders.
wtdpapb Creates input for the stochastic dominance function stochdom2