错误于UseMethod("npplot", bws) : 如何解决？

相似文件 换一批

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

> #China production function noparametric estimate
> rt<-read.table("china.txt",header=TRUE); rt
   year   realgdp  capital labor
1  1979  4016.290   4493.1 41024
2  1980  4194.429   5152.7 42361
3  1981  4460.196   5835.5 43725
4  1982  4882.096   6700.4 45295
5  1983  5322.089   7794.1 46436
6  1984  6135.583   9123.9 48197
7  1985  6923.494  10893.4 49873
8  1986  7522.190  12877.9 51282
9  1987  8195.861  14889.5 52783
10 1988  8645.281  16957.5 54334
11 1989  8247.404  18431.3 55329
12 1990  8940.758  19783.6 56740
13 1991 10088.204  21428.6 58360
14 1992 11577.152  23813.8 59432
15 1993 13525.485  27064.5 60220
16 1994 14813.392  30770.9 61470
17 1995 15927.664  34712.5 67947
18 1996 17251.361  38966.8 68850
19 1997 18478.955  43547.6 69600
20 1998 19738.047  48916.7 69957
21 1999 21046.761  54518.2 71394
22 2000 22753.226  60400.8 72085
23 2001 24936.476  67044.9 73025
24 2002 27762.468  74964.9 73740
25 2003 31091.589  84902.1 74432
26 2004 35164.634  95584.3 75200
27 2005 40237.263 108940.2 75825
> y=log((rt$realgdp/rt$labor)*10000)
> x=log((rt$capital/rt$labor)*10000)
>
>
> #package np, nonparametric and semiparametric kernel methods
> library(np)
> h1=npregbw(formula=y~x); h1

Multistart 1 of 1 |
Multistart 1 of 1 |
Multistart 1 of 1 |
Multistart 1 of 1 /
Multistart 1 of 1 |
Multistart 1 of 1 |
                  

Regression Data (27 observations, 1 variable(s)):

                       x
Bandwidth(s): 0.06893708

Regression Type: Local-Constant
Bandwidth Selection Method: Least Squares Cross-Validation
Formula: y ~ x
Bandwidth Type: Fixed
Objective Function Value: 0.001361645 (achieved on multistart 1)

Continuous Kernel Type: Second-Order Gaussian
No. Continuous Explanatory Vars.: 1

> fit1<-npreg(bws=h1,txdat=x,tydat=y)
> npplot(x,y)
错误于UseMethod("npplot", bws) :
  "npplot"没有适用于"c('double', 'numeric')"目标对象的方法
> points(x,y)
错误于plot.xy(xy.coords(x, y), type = type, ...) : 还没有调用plot.new
>
> #package KernSmooth, local linear regression
> library(KernSmooth)
> h2=dpill(x,y); h2
[1] 0.8108148
> fit2<-locpoly(x,y,bandwidth=h2)
> plot(x,y)
> lines(fit2)
> #first order derivatives
> order1<-locpoly(x,y,bandwidth=h2,drv=1)
> plot(order1$x,order1$y,type='l')
>
>
> #semiparametric regression, package np
> y1=log(rt$realgdp*100000000)
> x1=log(rt$labor*10000)
> x2=log(rt$capital*100000000)
>
> h3<-npplregbw(y1~x1|x2); h3

Multistart 1 of 1 |
Multistart 1 of 1 |
Multistart 1 of 1 |
Multistart 1 of 1 /
Multistart 1 of 1 |
Multistart 1 of 1 |
                  

Multistart 1 of 1 |
Multistart 1 of 1 |
Multistart 1 of 1 |
Multistart 1 of 1 /
Multistart 1 of 1 |
Multistart 1 of 1 |
                  

Partially Linear Model
Regression data (27 observations,
1 linear parametric variable(s) 1 nonparametric variable(s):
                   y(z)
Bandwidth(s): 0.0753333

                    x(z)
Bandwidth(s): 0.08117952

Regression Type: Local-Constant
Bandwidth Selection Method: Least Squares Cross-Validation
Formula: y1 ~ x1 | x2
Bandwidth Type: Fixed

Continuous Kernel Type: Second-Order Gaussian
No. Continuous Explanatory Vars.: 1

> #h3<-npplregbw(xdat=x1,ydat=y1,zdat=x2); h3
> fit3<-npplreg(bws=h3)
> summary(fit3)

Partially Linear Model
Regression data: 27 training points, in 2 variable(s)
With 1 linear parametric regressor(s), 1 nonparametric regressor(s)

                   y(z)
Bandwidth(s): 0.0753333

                    x(z)
Bandwidth(s): 0.08117952

                       x1
Coefficient(s): 0.5709484

Kernel Regression Estimator: Local-Constant
Bandwidth Type: Fixed

Residual standard error: 0.0001465206
R-squared: 0.999693

Continuous Kernel Type: Second-Order Gaussian
No. Continuous Explanatory Vars.: 1

> coef(fit3)
       x1
0.5709484
> npplot(bws=h3)
>

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏0 回帖

关键词：Method plot SEM ETH EME function library capital methods package

zhangtao兄
你是不是要画这样的图?

plot(h1)
points(x,y)

#There is no need to call npplot directly as it is automatically invoked
   when plot is used with an object generated by the np package.

楼主，我跟你出现的问题一样的，楼上的方法可以用下哦。还有最后的结果> coef(fit3)
       x1
0.5709484

是不是跟资料上的不同lnY = 0.0966378 ln L + m(ln K)？？画出来的m(ln K)图形也不一样，请问楼主知道原因么，谢谢先，

epoh 发表于 2012-10-23 08:01
zhangtao兄
你是不是要画这样的图?

太好了，我正在研究非参数曲线拟合，请问可以把程序发给我看看吗？