Linked Questions

6 votes
1 answer
653 views

State of the art: Non-parametric density estimation with a boundary and data clumped near zero [duplicate]

I have some data which I wish to estimate the marginal distribution of. I have no real idea what parametric distribution would be suitable, so was planning on fitting a non-parametric (probably kernel)...
GeorgeWilson's user avatar
0 votes
0 answers
156 views

Log transformation in R (Precipitation Data) [duplicate]

In many situations the values that a random variable, X, can take on is restricted, for example precipitation data [0,inf), that is f(x) = 0 for x < 0. We say that the support of f(x) is [0,inf). ...
Rosbert's user avatar
  • 63
0 votes
0 answers
79 views

Kernel density estimation for a variable with lots of zeros [duplicate]

I am trying to estimate the kernel density for number of days a child is sick. Around 73% of children report not being sick, i.e. zero. How do I estimate a kernel density for this censored variable ...
user30800's user avatar
0 votes
0 answers
40 views

Non-Parametric Density estimation with a positive variable [duplicate]

I’m struggling to find a way to represent a kernel density estimation with a nonnegative random variable. I have read a couple of articles tackling this issue; however I couldn’t implement it in R. I ...
Francisco's user avatar
13 votes
4 answers
3k views

How can I estimate the density of a zero-inflated parameter in R?

I have a data set with lots of zeros that looks like this: set.seed(1) x <- c(rlnorm(100),rep(0,50)) hist(x,probability=TRUE,breaks = 25) I would like to draw ...
Abe's user avatar
  • 3,841
0 votes
1 answer
14k views

"Negative density" for non-negative variables [closed]

Having an integer positive variable (number of days) in an experiment, I got negative values for the kernel density plots using R. I have read other posts relating to this topic. They admitted that ...
user30314's user avatar
  • 103
11 votes
2 answers
2k views

Kernel density estimation and boundary bias

What sort of kernel density estimator does one use to avoid boundary bias? Consider the task of estimating the density $f_0(x)$ with bounded support and where the probability mass is not decreasing ...
Jesper for President's user avatar
2 votes
2 answers
8k views

Does this graph follow a exponential distribution or a log-normal?

command for the graph: hist(c1,freq=FALSE) lines(density(c1,adjust=2),col="darkblue",lwd=2) I generated this sequence in R: ...
Joao ricardo's user avatar
12 votes
2 answers
2k views

Kernel density estimation on asymmetric distributions

Let $\{x_1,\ldots,x_N\}$ be observations drawn from an unknown (but certainly asymmetric) probability distribution. I would like to find the probability distribution by using the KDE approach: $$ \...
Eleanore's user avatar
  • 233
4 votes
3 answers
897 views

Information loss by histograms

Recently I became curious about what I imagine to be an old problem: the fidelity of histograms to an underlying data set. CrossValidated has a number of questions on the subject of "optimal ...
chepyle's user avatar
  • 161
2 votes
1 answer
2k views

Why density plot tails are beyond maximum and minimum values?

I am trying to interpret the tails of a density curve, which go beyond xlims(0 in this case). I understand that area under the curve between any two points represents the probability of that event. ...
Yogesh's user avatar
  • 121
3 votes
1 answer
1k views

Why simulated gamma distributed data have negative kernel values?

I know that Gamma distribution does not allow 0 or negative values. I was doing some simulation and when I write this code in R ...
Filippo's user avatar
  • 349
2 votes
2 answers
448 views

downsampling a kde / combining kde and histogram

I'm calculating a KDE of one parameter (y, particle density) in bins of another parameter (x, distance from the origin). At ...
DilithiumMatrix's user avatar
1 vote
0 answers
294 views

Weighted density estimation of exponentially distributed RV [closed]

I am trying to get a weighted density estimation of some data. Unfortunately, the data is approximately exponentially distributed after the weight transform, which gives a false sense of positive ...
cel's user avatar
  • 119
1 vote
0 answers
210 views

strange density plot of p-value [duplicate]

I computed the T-score and P-value using t.test() for my data, and finally I've plotted the density of my p-value and I've got strange plot. I don't know, why I see ...
user2806363's user avatar
  • 2,743

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