Changing charts of a regression

Question

I’m trying to modify the chart of the Tables of this regression that I’ve been around:

x

c(-0.0179316822180174, -0.00641604898349779, 0.0118829440361971, 
-0.00821159118344772, -0.0171607214317729, 0.0162441460856755, 
0.00963105000906578, 0.00394937550015284, -0.0373589167442337, 
-0.00470636563065663, 0.0236590046189202, 0.0063475614358427, 
-0.0070059434857957, -0.0169201469608903, 0.00155616011324267, 
0.0249988251813635, -0.0229110197078823, 0.0196769910169684, 
-0.0232707200733515, -0.0147603533337192, 0.0146431308369133, 
0.014497826586643, -0.00797107471083758, 0.0127135417735376, 
0.0251444784676054, -0.00765473955145302, 0.00261176732854917, 
0.00422561863994186, 0.0169941535677274, -0.0273569406032738, 
0.00744049850761097, -0.0239050021435552, 0.00364945909804465, 
0.0298095264998562, -0.0118560732543823, -0.00568936398070341, 
0.0263777219741199, -0.01045817176334, 0.0193070220281141, 0.0458305554890071, 
-0.0127560808477733, 0.0107511726413252, 0.0289323343688418, 
-0.0160308496643017, 0.0180222017522788, 0.0240456896851978, 
-0.0523667660813357, 0.0221451602414924, 0.0129487350977803, 
0.0143767869461501, -0.00637530773247202, 0.00715694081686963, 
0.010049767615021, -0.0132797307956235, -0.0175982918196536, 
-0.0131551067453106, 0.0105408021133636, 0.0195710544478027, 
-0.0203275721747587, 0.0293425895382764, -0.000777621507193182, 
-0.00675534408376044, -0.0231203355600037, -0.0040448935503764, 
-0.0409024741790648, -0.0245661039171186, 0.00984019692277266, 
-0.0164702632938923, 0.00516051244449134, 0.00544526835976067, 
-0.0340426755099334, -0.0207890109659793, 0.0426363179214442, 
-0.00351865802118057, -0.0110782883419167, -0.024773727630523, 
-0.00716884307950422, 0.0262043639376453, 0.0161207659146274, 
-0.0491302988818763, -0.0211728961394305, -0.0133934386752423, 
-0.0400734284906117, -0.0166611855989933, -0.0193531306066065, 
0.00971419325460077, 0.0357254985156947, -0.0333207907402884, 
0.0109406291684547, -0.00272395613977894, 0.0107796305168576, 
-0.00588183923966368, -0.012491285708382, -0.0423110888432794, 
-0.00438693819528468, 0.0177541412380439, -0.020772938896655, 
0.0189228345365723, -0.0106763932048778, 0.0468064583053511)

y

   c(0.000576738240914476, 0.000538252649209758, 0.000328347920403316, 
0.000551536204488168, 0.000621483730588512, 0.00091495119712004, 
0.00109651825560558, 0.00123180669729761, 0.00129148926642808, 
0.00129037681820299, 0.00134693760472337, 0.00156192230364605, 
0.00142144112291509, 0.00154651078830825, -0.000167473330263679, 
0.00195431640270072, 0.00145027931070263, 0.00364735971060892, 
-0.00096570131327478, 0.00926719634555029, -0.00233090423778703, 
0.00169002340998969, -0.0018999947889875, -0.00321632100485059, 
0.000738983028809759, 0.000560542619919058, 0.000774568378244744, 
-0.000434821126273743, 0.000881431501733143, -0.00244624308218078, 
0, 0.0125279278690494, 0.00185927179999512, -3.28186278559794e-05, 
-0.00589444451637772, -0.00014506419115895, 0.000891099594783507, 
-0.00695464873509455, 0.000574144381182862, -0.000156492073995818, 
-0.00239438631071848, -0.00471931618926341, -0.00481921408324487, 
-0.00081512646250681, -0.000502817266098854, -0.0011187389928583, 
-0.00434727701657506, -0.000627596326747082, 0.00055506055967075, 
0.000490259703263163, 0.000440631958631366, -0.00332497619117139, 
-0.000767416119292985, 0.00109638345042196, 0.00172299673107124, 
0.00179699775909237, 0.00167405836622925, 0.000276277238694167, 
0.00419818885099232, 0.00675923261514455, 0.0016239844842349, 
0.000268701255320192, 0.00176419582798132, 0.00206722933963693, 
0.000731336330279664, 0.00182748588872217, -0.00411706814274904, 
0.00176192435305844, 0.0146897325351242, 0.00640952859808785, 
0.00216051625545427, 0.00587491055544875, -4.93125015511575e-05, 
-0.000330825886204311, 0.0100184061569999, 0.00681726701302382, 
0.00189868295029555, 0.00187938991649916, -0.0039783258159809, 
0.00203838232559217, 0.00295293766227511, -5.09100165567711e-05, 
0.00223329417681417, 0.00784583472285028, 0.00229086844066151, 
0.00257624622374575, 0.0088559303832999, 0.000833133961172683, 
0.00274639936803289, 0.00589460164436073, 0.00276022547587274, 
0.00550758009795338, 0.00796644625557363, 0.0022694837516456, 
0.0114793057877365, 0.00134302892350002, 0.00333286567514701, 
0.00721456781660945, 0.00512657322727417, 0.00154581658468977
)


fit1 <- rq(y ~ x, tau=seq(0.05, 0.95, by = 0.05))

summary<-summary(fit1,se="iid")

plot(summary,parm=2,ylab="beta",xlab = "tau", cex = 1, pch = 20)

On Plot I have several polka dots representing the esteemed buns.

How do I change these balls by making certain balls (I see this using the command summary) are asterisks and other triangles?

Answer 1

Just change the pch argument of your Plot. For example,

plot(fit1.summary, parm=2, ylab="beta", cex=1, xlab = "tau", pch = c(rep(c(2, 8), 7), 2))

Just adjust the vector with the pch values so that each beta is represented with the correct symbol.

Answer 2

Assign an array to the parameter pch:

library(quantreg)

## Ajuste da regressão quantílica
seqt <- seq(0.1, 0.9, by = 0.05)
fit1 <- rq(dist ~ speed, tau = seqt, data = cars)
resu <- summary(fit1,se="iid")

## Um 'plotting character' (pch) para cada theta
plot(resu, parm = 1, ylab = "beta", xlab = "tau",
     cex = 1, pch = seq_along(seqt))

## Um 'plotting character' (pch) distinto para os thetas em que
## a estatística t do intercepto é maior de |1.96|
ind <-  sapply(resu, function(x) 
    abs(x$coef["(Intercept)", "t value"]) < 1.96)
plot(resu, parm = 1, ylab = "beta", xlab = "tau",
     cex = 1, pch = ifelse(ind, 8, 19))

Answer 3

Here’s a try to copy this chart:

fit1 <- rq(y ~ x, tau=seq(0.05, 0.95, by = 0.05))

library(ggplot2)
library(dplyr)
library(broom)

broom::tidy(fit1) %>%
  filter(term == "x") %>%
  mutate(shape = ifelse(row_number() %in% c(1, 5, 7), "a", "b")) %>%
  ggplot(aes(x = tau, y = estimate)) + 
  geom_ribbon(aes(ymin = conf.low, ymax = conf.high), alpha = 0.2) +
  geom_point(aes(shape = shape)) + 
  geom_hline(aes(yintercept = mean(estimate)), colour = "red") +
  geom_hline(aes(yintercept = quantile(estimate, probs = 0.05)), colour = "red", linetype = "dashed") +
  geom_hline(aes(yintercept = quantile(estimate, probs = 0.95)), colour = "red", linetype = "dashed")

Here’s the original graph. Note that the red lines are not the same... I’m not sure what they represent, but you can try adjusting. In the code this is very simple to modify.