程序代写代做代考 Goodness-of-fit example

Goodness-of-fit example

Three Point Process Datasets

Time (sec)

Dataset 1:

Dataset 2:

Dataset 3:

Poisson Likelihood

0 5 10 15 20 25 30 35 40 45 50
0

2

4

6

8

10

12

14
x 1023

Lambda (Hz)

L
ik

el
ih

oo
d

( )

Spike Train Data

Time (sec)

Dataset 1:

Dataset 2:

Dataset 3:

Waiting Time Data

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
0

0.5

1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
0

10

20

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
0

0.5

1

Time (sec)

Dataset 1:

Dataset 2:

Dataset 3:

Waiting Time Histograms

Dataset 1: Dataset 2: Dataset 3:

Waiting Time (sec) Waiting Time (sec) Waiting Time (sec)

C
ou

nt
s

0.04

Empirical Distributions

0 0.05 0.1 0.15 0.2 0.25
0

0.2

0.4

0.6

0.8

1

0 0.05 0.1 0.15 0.2 0.25
0

0.2

0.4

0.6

0.8

1

0 0.05 0.1 0.15 0.2 0.25
0

0.2

0.4

0.6

0.8

1

Waiting Time (sec)

KS Plots

Empirical CDF Empirical CDF Empirical CDF

M
od

el
C

D
F

Dataset 1: Dataset 2: Dataset 3:

KS Plots

Empirical CDF Empirical CDF Empirical CDF

M
od

el
C

D
F

Dataset 1: Dataset 2: Dataset 3:

KS Stat = 0.126 KS Stat = 0.632 KS Stat = 0.312

QQ Plots

Empirical Quantiles Empirical Quantiles Empirical Quantiles

M
od

el
Q

ua
nt

ile
s

Dataset 1: Dataset 2: Dataset 3:

Waiting Time Autocorrelation Functions

Dataset 1: Dataset 2: Dataset 3:

Lag Lag Lag

Fano Factor (1 msec bins)

Time (sec)

FF1,FF2,FF3

Fano Factor (40 msec bins)

FF1FF2 FF3
Time (sec)

Summary

Hist KS QQ Fano Factor ACF

Dataset 1 P P P P P

Dataset 2 X X
All

Quantiles
0.04

X X

Dataset 3 P X
Off by

Factor of
2

P P

Spike Train Data

Time (sec)

Dataset 1:

Dataset 2:

Dataset 3: