# date     notkept hosts
1399003199 50      10
1399089599 63      11
1399175999 120     12
1399262399 55      20
1399348799 60      22
1399435199 63      25
1399521599 52      24

##</code><code>##

!/usr/bin/gnuplot

set xlabel "Date"
set ylabel "Count"

set autoscale
p(x) = m1*x + b1
fit p(x) 'test.dat' using 1:2 via m1, b1

plot 'test.dat' using 1:2, p(x)

##</code><code>##

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

m1              = 4.65548e-08      +/- 5.823e-05    (1.251e+05%)
b1              = 1                +/- 8.148e+04    (8.148e+06%)

##</code><code>##

#!/usr/bin/gnuplot

set xlabel "Date"
set ylabel "Count"

set autoscale

p(x) = m1*x + b1
m1 = -1e-5
b1 = 30000
fit p(x) 'test.dat' using 1:2 via m1, b1

plot 'test.dat' using 1:2, p(x)

##</code><code>##

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

m1              = -2.13926e-05     +/- 5.736e-05    (268.1%)
b1              = 30000            +/- 8.027e+04    (267.6%)

##</code><code>##

#!/usr/bin/gnuplot

set xlabel "Date"
set ylabel "Count"

set autoscale

p(x) = m1 * (x / 1399003199)  + b1
fit p(x) 'test.dat' using 1:2 via m1, b1

plot 'test.dat' using 1:2, p(x)

##</code><code>##

Final set of parameters            Asymptotic Standard Error
=======================            ==========================

m1              = -31227.8         +/- 8.025e+04    (257%)
b1              = 31299.7          +/- 8.026e+04    (256.4%)

##</code><code>##

> x
[1] 1399003199 1399089599 1399175999 1399262399 1399348799
[6] 1399435199 1399521599
> y
[1]  50  63 120  55  60  63  52
> lm(y ~ x)

Call:
lm(formula = y ~ x)

Coefficients:
(Intercept)            x  
  3.130e+04   -2.232e-05

> m <- lm(y ~ x)
> summary(m)

Call:
lm(formula = y ~ x)

Residuals:
       1        2        3        4        5        6        7 
-21.9286  -7.0000  51.9286 -11.1429  -4.2143   0.7143  -8.3571 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  3.130e+04  8.026e+04   0.390    0.713
x           -2.232e-05  5.736e-05  -0.389    0.713

Residual standard error: 26.22 on 5 degrees of freedom
Multiple R-squared:  0.0294,	Adjusted R-squared:  -0.1647 
F-statistic: 0.1514 on 1 and 5 DF,  p-value: 0.7132