R Graphical Manual

Browse All

Last data update: 2014.03.03

R: Arrival target setting using SF

target.arrival.sf

R Documentation

Arrival target setting using SF

Description

Employs dm.sf over time to estimate the arrival of known specifications. This function is valid only when multiplicative form of directional vector is used.

Usage

target.arrival.sf(xdata, ydata, date, t, rts, g, w=NULL, sg="ssm", ftype="d")

Arguments

`xdata`	Input(s) vector (n by m)
`ydata`	Output(s) vector (n by s)
`date`	Production date (n by 1)
`t`	A vantage point from which the RoC is captured
`rts`	Returns to scale assumption `"crs"` Constant RTS `"vrs"` Variable RTS `"irs"` Increasing RTS `"drs"` Decreasing RTS
`g`	Directional vector indicating a measurement direction (n by (m+s))
`w`	Weak disposability vector indicating (an) undesirable output(s) (1 by s)
`sg`	Employs second-stage optimization `"ssm"` Slack-sum maximization (default) `"max"` Date-sum maximization `"min"` Date-sum minimization
`ftype`	Frontier type `"d"` Dynamic frontier (default) `"s"` Static frontier

Value

`$eff_t`	Efficiency at `t`
`$lambda_t`	Intensity vector at `t`
`$eft_date`	Effective date
`$roc_avg`	Average RoC
`$roc_local`	Local RoC
`$roc_ind`	Individualized RoC
`$arrival_avg`	Estimated arrival using `roc_avg`
`$arrival_seg`	Estimated arrival using `roc_ind`

Author(s)

Dong-Joon Lim, PhD

References

Lim, Dong-Joon, et al. "Comparing technological advancement of hybrid electric vehicles (HEV) in different market segments." Technological Forecasting and Social Change 97 (2015): 140~153.

Lim, Dong-Joon, and Timothy R. Anderson. Time series benchmarking analysis for new product scheduling: who are the competitors and how fast are they moving forward?. Advances in DEA Theory and Applications: with Examples in Forecasting Models. Wiley (forthcoming), 2016.

Examples

# Estimate arrivals of MY2013 hev models
  # Load hev dataset
  data(dataset.hev.2013)
  
  # ready
  x<-subset(dataset.hev.2013,select=3)
  y<-subset(dataset.hev.2013,select=4:6)
  d<-subset(dataset.hev.2013,select=2)
  g<-data.frame(x,y)
  
  # go
  target.arrival.sf(x,y,d,2012,"vrs",g)$arrival_seg

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DJL)
Loading required package: car
Loading required package: combinat

Attaching package: 'combinat'

The following object is masked from 'package:utils':

    combn

Loading required package: lpSolveAPI
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DJL/target.arrival.sf.Rd_%03d_medium.png", width=480, height=480)
> ### Name: target.arrival.sf
> ### Title: Arrival target setting using SF
> ### Aliases: target.arrival.sf
> 
> ### ** Examples
> 
> # Estimate arrivals of MY2013 hev models
>   # Load hev dataset
>   data(dataset.hev.2013)
>   
>   # ready
>   x<-subset(dataset.hev.2013,select=3)
>   y<-subset(dataset.hev.2013,select=4:6)
>   d<-subset(dataset.hev.2013,select=2)
>   g<-data.frame(x,y)
>   
>   # go
>   target.arrival.sf(x,y,d,2012,"vrs",g)$arrival_seg
           [,1]
  [1,]       NA
  [2,]       NA
  [3,]       NA
  [4,]       NA
  [5,]       NA
  [6,]       NA
  [7,]       NA
  [8,]       NA
  [9,]       NA
 [10,]       NA
 [11,]       NA
 [12,]       NA
 [13,]       NA
 [14,]       NA
 [15,]       NA
 [16,]       NA
 [17,]       NA
 [18,]       NA
 [19,]       NA
 [20,]       NA
 [21,]       NA
 [22,]       NA
 [23,]       NA
 [24,]       NA
 [25,]       NA
 [26,]       NA
 [27,]       NA
 [28,]       NA
 [29,]       NA
 [30,]       NA
 [31,]       NA
 [32,]       NA
 [33,]       NA
 [34,]       NA
 [35,]       NA
 [36,]       NA
 [37,]       NA
 [38,]       NA
 [39,]       NA
 [40,]       NA
 [41,]       NA
 [42,]       NA
 [43,]       NA
 [44,]       NA
 [45,]       NA
 [46,]       NA
 [47,]       NA
 [48,]       NA
 [49,]       NA
 [50,]       NA
 [51,]       NA
 [52,]       NA
 [53,]       NA
 [54,]       NA
 [55,]       NA
 [56,]       NA
 [57,]       NA
 [58,]       NA
 [59,]       NA
 [60,]       NA
 [61,]       NA
 [62,]       NA
 [63,]       NA
 [64,]       NA
 [65,]       NA
 [66,]       NA
 [67,]       NA
 [68,]       NA
 [69,]       NA
 [70,]       NA
 [71,]       NA
 [72,]       NA
 [73,]       NA
 [74,]       NA
 [75,]       NA
 [76,]       NA
 [77,]       NA
 [78,]       NA
 [79,]       NA
 [80,]       NA
 [81,]       NA
 [82,]       NA
 [83,]       NA
 [84,]       NA
 [85,]       NA
 [86,]       NA
 [87,]       NA
 [88,]       NA
 [89,]       NA
 [90,]       NA
 [91,]       NA
 [92,]       NA
 [93,]       NA
 [94,]       NA
 [95,]       NA
 [96,]       NA
 [97,]       NA
 [98,]       NA
 [99,]       NA
[100,]       NA
[101,]       NA
[102,]       NA
[103,]       NA
[104,]       NA
[105,]       NA
[106,]       NA
[107,]       NA
[108,]       NA
[109,]       NA
[110,]       NA
[111,]       NA
[112,]       NA
[113,]       NA
[114,]       NA
[115,]       NA
[116,]       NA
[117,]       NA
[118,]       NA
[119,]       NA
[120,]       NA
[121,]       NA
[122,]       NA
[123,]       NA
[124,]       NA
[125,]       NA
[126,]       NA
[127,]       NA
[128,]       NA
[129,]       NA
[130,]       NA
[131,]       NA
[132,]       NA
[133,]       NA
[134,]       NA
[135,]       NA
[136,]       NA
[137,]       NA
[138,]       NA
[139,]       NA
[140,]       NA
[141,]       NA
[142,]       NA
[143,]       NA
[144,]       NA
[145,] 2012.230
[146,]       NA
[147,]       NA
[148,]       NA
[149,]       NA
[150,]       NA
[151,] 2012.197
[152,] 2014.170
[153,] 2014.170
[154,] 2012.002
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>