ede | R Documentation |
Implementation of EDE method as defined in [1] and [2] by giving a simple output of the method.
ede(x, y, index)
x |
The numeric vector of x-abscissas, must be of length at least 4. |
y |
The numeric vector of the noisy or not y-ordinates, must be of length at least 4. |
index |
If data is convex/concave then index=0 |
We also obtain the x_{F_{1}},x_{F_{2}} points, see [1], [2].
A matrix of size 1 x 3 is returned with elements:
A(1,1) |
The index j_{F_{1}} for EDE method |
A(1,2) |
The index j_{F_{2}} for EDE method |
A(1,3) |
The Extremum Distance Estimator (EDE) for inflection point |
This function is for real big data sets, more than one million rows. It is the fastest available method, see [2] for comparison to other methods.
Demetris T. Christopoulos
[1]Demetris T. Christopoulos (2014). Developing methods for identifying the inflection point of a convex/concave curve. arXiv:1206.5478v2 [math.NA]. https://arxiv.org/pdf/1206.5478v2.pdf
[2]Demetris T. Christopoulos (2016). On the efficient identification of an inflection point.International Journal of Mathematics and Scientific Computing, (ISSN: 2231-5330), vol. 6(1). https://veltech.edu.in/wp-content/uploads/2016/04/Paper-04-2016.pdf
See also the iterative version bede
and iterations plot using findipiterplot
.
# #Fisher-pry model with heavy noise, unequal spaces #and 1 million cases: N=10^6+1; set.seed(2017-05-11);x=sort(runif(N,0,10));y=5+5*tanh(x-5)+runif(N,-1,1); # ptm <- proc.time() tede=ede(x,y,0);tede;proc.time() - ptm # j1 j2 chi # EDE 351061 648080 4.997139 # user system elapsed # 0.01 0.00 0.01 #
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