ECGr {ECG}R Documentation

Creates an ECGr object

Description

Builds an ECGr object to estimate an extrapolation of the local minimum in the response for a series of replicated observations.

Usage

ECGr(data, from=min(data$x), to=max(data$x), columns, useConstantDelta=FALSE, 
	maxResponseFraction=0.5, minResponseFraction=0.05, 
	byResponseFraction=-0.05, fixedResponseFraction=0.5, 
	useFixedResponseFraction = FALSE, replaceOutliers = TRUE, 
	responseLowerLimit = min(data[, columns]), 
	responseUpperLimit = max(data[, columns]),
	alpha=0.05, kp=if(length(columns)<=1) qnorm(1-alpha/2) else 
		qt(1-alpha/2, length(columns)-1), 
	signifDigits = 2, useRobustStatistics=TRUE, ...)

Arguments

data

a data frame structure containing (date, x, y1, ..., yn) columns, it may contain some other columns.

from

a numeric value with the initial value of x to search for a local minimum.

to

a numeric value with the final value of x to search for a local minimum.

columns

a vector of indexes of the columns to be considered in the profile.

useConstantDelta

a logical value, if true then it uses the mean value of the differences in x, otherwise, it uses the differences in x to estimate the expected value. in the analysis.

maxResponseFraction

a real value with the fraction (0,1) of the maximum height to be considered in the analysis.

minResponseFraction

a real value with the fraction (0,1) of the minimum height to be considered in the analysis.

byResponseFraction

a real value with the fraction (0,1) of the decrement of height to be considered in the analysis. The extrapolation analysis uses the sequence: maxResponseFraction, maxResponseFraction+byResponseFraction, ..., minResponseFraction

fixedResponseFraction

a numeric with the fraction of hieght to be used as a reference to normilize.

useFixedResponseFraction

a logical value, if true then it uses the value of f.fixed to normalize all the computations, otherwise it uses the values of extrapolation sequence of fractions to normalize.

replaceOutliers

a logic value, if true then it uses the value of responseLowerLimit and responseUpperLimit to replace outlier values. Default value is TRUE.

responseLowerLimit

a real value to be used as the default to replace outlier values lower than expected, its default value is 0.

responseUpperLimit

a real value to be used as the default to replace outlier values larger than expected, its default value is 1.

alpha

a real value, define the level of significance for building confidence interval.

kp

a real value, it defines the coverage factor to be used to estimate the expanded uncertainty. It is build based on the level of significance alpha and assumes normal distribution of the error terms, its default value is qnorm(1-alpha/2).

signifDigits

number of significant digits used to display the result.

useRobustStatistics

a logical value, if true then median and mad are used to estimate location and dispersion otherwise the mean and standard deviation are used.

...

additional parameters.

Value

x

numeric, the estimated value

u

numeric, the estimated uncertainty associated to x

input

list, contains the input parameters

frame

list, contains the reference values of the analysis. This information is used to build a verbosed version of its plot. The content of the list is:
y average of the response series. Depending on the useRobustStatistics value the average can be the mean or the median of the series indicated in the columns parameter. u.y average uncertainty of the response series. Depending on the useRobustStatistics value the average can be the standard deviation or the median absolute deviation of the series indicated in the columns parameter. kp the updated coverage factor considering the reduced degrees of freedom from using the model used.

x.summary the estimated location from the average of the series.
u.x.summary the estimated uncertainty associated to the estimated location from the average of the series.

details the matrix containing the results for considered fractions in the analysis. The columns are:
the estimated location, the estimated uncertainty, the minimum response value found,
the minimum value of the location estimates, the maximum value of the location estimates,
the estimated coverage factor.
used.data.points the number of data points used in the estimations.

Author(s)

H. Gasca-Aragon

See Also

See Also as ECGdata, print.ECGr, plot.ECGr

Examples

require(ECG)
N<- 1000
set.seed(12345)
d1<- 1-sin(seq(1:(5/2*N))/N*pi-pi*3/4)+rnorm(5/2*N, 0, 0.01)
d2<- 1-sin(seq(1:(5/2*N))/N*pi-pi*3/4)+rnorm(5/2*N, 0, 0.01)
dat<- data.frame(x=1:length(d1), 
	y1=100*(d1-min(d1))/(max(d1)-min(d1)),
	y2=100*(d2-min(d2))/(max(d2)-min(d2))
)
ECGres<- ECGr(dat, columns=c(2,3))
ECGres

[Package ECG version 0.5.2 Index]