复现步骤

age <- c(
  40, 38, 40, 35, 36, 37, 41, 40, 37, 38, 40, 38,
  40, 36, 40, 38, 42, 39, 40, 37, 36, 38, 39, 40
)
birthw <- c(
  2968, 2795, 3163, 2925, 2625, 2847, 3292, 3473, 2628, 3176,
  3421, 2975, 3317, 2729, 2935, 2754, 3210, 2817, 3126, 2539,
  2412, 2991, 2875, 3231
)
sex <- gl(2, 12, labels = c("M", "F"))
BirthWeight <- data.frame(age = age, birthw = birthw, sex = sex)

library(ggplot2)
ggplot(aes(x = age, y = birthw, group = sex, color = sex), 
       data = BirthWeight) + geom_point() +
  geom_smooth(method = "loess")

lowess(age[sex == "M"], birthw[sex == "M"])

$x
 [1] 35 36 37 37 38 38 38 40 40 40 40 41

$y
 [1] 2760.981 2791.348 2823.453 2823.453 2981.416 2981.416 2981.416 3262.513
 [9] 3262.513 3262.513 3262.513 3292.000

lowess(age[sex == "F"], birthw[sex == "F"])

$x
 [1] 36 36 37 38 38 39 39 40 40 40 40 42

$y
 [1] 2535.244 2535.244 2658.669 2775.027 2775.027 2846.000 2846.000 3162.843
 [9] 3162.843 3162.843 3162.843 3248.897

经查 ?loess 和 ?lowess，前者是后者的的扩展版，二者默认设置有所不同。现在的问题是我没办法对应二者在参数设置上的关系，求助各位？

附上 ggplot2 和运行环境

xfun::session_info('ggplot2')
R Under development (unstable) (2019-10-24 r77329)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 8.1 x64 (build 9600)

Locale:
  LC_COLLATE=Chinese (Simplified)_China.936 
  LC_CTYPE=Chinese (Simplified)_China.936   
  LC_MONETARY=Chinese (Simplified)_China.936
  LC_NUMERIC=C                              
  LC_TIME=Chinese (Simplified)_China.936    

Package version:
  assertthat_0.2.1   backports_1.1.5    cli_1.1.0         
  colorspace_1.4.1   crayon_1.3.4       digest_0.6.22     
  ellipsis_0.3.0     fansi_0.4.0        ggplot2_3.2.1.9000
  glue_1.3.1         graphics_4.0.0     grDevices_4.0.0   
  grid_4.0.0         gtable_0.3.0       labeling_0.3      
  lattice_0.20.38    magrittr_1.5       MASS_7.3.51.4     
  Matrix_1.2.17      methods_4.0.0      mgcv_1.8.30       
  munsell_0.5.0      nlme_3.1.141       pillar_1.4.2      
  pkgconfig_2.0.3    plyr_1.8.4         R6_2.4.0          
  RColorBrewer_1.1.2 Rcpp_1.0.2         reshape2_1.4.3    
  rlang_0.4.1        scales_1.0.0       splines_4.0.0     
  stats_4.0.0        stringi_1.4.3      stringr_1.4.0     
  tibble_2.1.3       tools_4.0.0        utf8_1.1.4        
  utils_4.0.0        vctrs_0.2.0        viridisLite_0.3.0 
  withr_2.1.2        zeallot_0.1.0

输出警告信息

Warning messages:
1: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  ... :
  pseudoinverse used at 38
2: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  ... :
  neighborhood radius 2
3: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  ... :
  reciprocal condition number  5.3401e-017
4: In predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)),  ... :
  pseudoinverse used at 38
5: In predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)),  ... :
  neighborhood radius 2
6: In predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)),  ... :
  reciprocal condition number  5.3401e-017
7: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  ... :
  pseudoinverse used at 40
8: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  ... :
  neighborhood radius 2
9: In simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  ... :
  reciprocal condition number  0
10: In predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)),  ... :
  pseudoinverse used at 40
11: In predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)),  ... :
  neighborhood radius 2
12: In predLoess(object$y, object$x, newx = if (is.null(newdata)) object$x else if (is.data.frame(newdata)) as.matrix(model.frame(delete.response(terms(object)),  ... :
  reciprocal condition number  0