absBstdres |
Block version of abs-stdres Absolute values of residuals of kernel regressions of standardized x on standardized y, no control variables. |
absBstdresC |
Block version of Absolute values of residuals of kernel regressions of standardized x on standardized y and control variables. |
absBstdrhserC |
Block version abs_stdrhser Absolute residuals kernel regressions of standardized x on y and control variables, Cr1 has abs(Resid*RHS). |
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) not gradients. |
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 (deprecated function). It is better to choose a target variable and pair it with all others, instead of considering all possible targets. |
badCol |
internal badCol |
bigfp |
Compute the numerical integration by the trapezoidal rule. |
bootGcLC |
Compute vector of n999 nonlinear Granger causality paths |
bootGcRsq |
Compute vector of n999 nonlinear Granger causality paths |
bootPairs |
Compute matrix of n999 rows and p-1 columns of bootstrap 'sum' (strength from Cr1 to Cr3). |
bootPairs0 |
Compute matrix of n999 rows and p-1 columns of bootstrap 'sum' index (strength from older criterion Cr1, with newer Cr2 and Cr3). |
bootQuantile |
Compute confidence intervals [quantile(s)] of indexes from bootPairs output |
bootSign |
Probability of unambiguously correct (+ or -) sign from bootPairs output |
bootSignPcent |
Probability of unambiguously correct (+ or -) sign from bootPairs output transformed to percentages. |
bootSummary |
Compute usual summary stats of 'sum' indexes from bootPairs output |
GcRsqX12 |
Granger nonlinear causality R^2 for x1=f(x1,x2), R^2 for flipped x1 and x2 and the difference between the two R^2 values |
GcRsqX12c |
Granger nonlinear causality R^2 for x1=f(x1,x2) minus R^2 for flipped 1 and 2 |
GcRsqYX |
Nonlinear Granger causality between two time series workhorse function. |
GcRsqYXc |
Nonlinear Granger causality between two time series workhorse function.(local constant version) |
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. |
getSeq |
Two sequences: starting+ending values from n and blocksize (internal use) |
gmc0 |
internal gmc0 |
gmc1 |
internal gmc1 |
gmcmtx0 |
Matrix R* of generalized correlation coefficients captures nonlinearities. |
gmcmtxBlk |
Matrix R* of generalized correlation coefficients captures nonlinearities using blocks. |
gmcmtxZ |
compute the matrix R* of generalized correlation coefficients. |
gmcxy_np |
Function to compute generalized correlation coefficients r*(x|y) and r*(y|x) from two vectors (not matrices) |
goodCol |
internal goodCol |
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. |
parcorBijk |
Block version of generalized partial correlation coefficients between Xi and Xj, after removing the effect of xk, via nonparametric regression residuals. |
parcorBMany |
Block version reports many generalized partial correlation coefficients allowing control variables. |
parcorMany |
Report many generalized partial correlation coefficients allowing control variables. |
parcorMtx |
Matrix of generalized partial correlation coefficients, always leaving out control variables, if any. |
parcorSilent |
Silently compute generalized (ridge-adjusted) partial correlation coefficients from matrix R*. |
parcor_ijk |
Generalized partial correlation coefficients between Xi and Xj, after removing the effect of xk, via nonparametric regression residuals. |
parcor_ijkOLD |
Generalized partial correlation coefficient between Xi and Xj after removing the effect of all others. (older version, deprecated) |
parcor_linear |
Partial correlation coefficient between Xi and Xj after removing the linear effect of all others. |
parcor_ridg |
Compute generalized (ridge-adjusted) partial correlation coefficients from matrix R*. (deprecated) |
pcause |
Compute the bootstrap probability of correct causal direction. |
pillar3D |
Create a 3D pillar chart to display (x, y, z) data coordinate surface. |
prelec2 |
Intermediate weighting function giving Non-Expected Utility theory weights. |
probSign |
Compute probability of positive or negative sign from bootPairs output |
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 |
siPairsBlk |
Block Version of silentPairs for causality scores with control variables |
some0Pairs |
Function reporting detailed kernel causality results in a 7-column matrix (uses deprecated criterion 1, no longer recommended but may be useful for second and third criterion typ=2,3) |
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, version 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.(deprecated) |
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. |
symmze |
Replace asymmetric matrix by max of abs values of [ij] or [ji] elements useful in symmetrizing gmcmtx0 general correlation matrix |