# All Questions

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### Simultaneous and Pointwise Confidence Bands for GAMs

I am performing a penalized B-spline regression on a simple time series of count data in R using the mgcv package. When I calculate a pointwise confidence band from the standard error of the fit based ...
31 views

### How are Markov chains used for time-series forecasting?

How are Markov chains used for time-series forecasting? Since the next state depends only on the current state, I would guess that I should first find the steady-state probabilities. To predict a ...
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### Expected count in Winbug

I have mortality count and total population of each counties of three states for 5 years. I want to get the expected count of mortality at each county and year to input in the Winbug. I wonder how ...
6 views

### Performance metrics, prioritizing based on impact

I apologize in advance for the poorly worded question. If anyone has any suggestions, please advise. Also, help with tagging appropriately would be appreciated. I'm collecting performance metrics ...
5 views

### Marginal means confidence interval

lets say that I have 4 groups and I want to report whether there are significant differences between them in a measured variables. Each group has different numbers of male/female and different ...
13 views

### How to determine if the errors made by the classifiers are uncorrelated

I am working on ensemble methods to improve the Area under the ROC curve in an experiment. In Ensemble Methods in Machine Learning ", Dietterich says " A necessary and suficient condition for an ...
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### What is the difference between kalman filter and extended kalman filter?

I am working SLAM based problems in robotics and I want to know whether I can use Kalman filter instead of the Extended kalman filter that is predominantly used ? If not, what is the difference?
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### Multiple Response Regression in Spark MLLib

I am trying to do a regression using RandomForests in Spark ML where I have several input variables and would like to predict several responses. Training data would look like X = ...
25 views

### kernel density estimation of the log-normal distribution

I stumbled upon the following issue I cannot make sense of: When using default choices, the KDE for a log-normal sample (green) does not look like a density that integrates to 1, compare the true ...
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### Time-series variable normalization before using state-space models

I try to estimate a time-series with an SSM that I built. The problem is that model fit is not very good and I think normalizing variables might help. Both my dependent of some of my independent ...
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### How MLN and MaxEnt are different?

To me it seems that MLN (Markov logic network) and MaxEnt (Maximum Entropy classifier) solve the same formula: $$p(y|x) = \frac{exp(\sum_i \lambda_if_i(x,y))}{\sum_y exp(\sum_i \lambda_if_i(x,y))}$$ ...
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### What happens to the coefficients when we switch labels (0/1) - in practice? [migrated]

I am trying to see in practice what was explained here what happens to the coefficients once labels are switched but I am not getting what is expected. Here is my attempt: I am using the example of ...
18 views

### Regression plot and function for: heavy-tailed probability distribution

I've got data points from a simulation as coordinates in a text-files like so: ...
14 views

### Binary logistic regression - SPSS

I did some regression analysis in SPSS using two binary variables: Biomarker X (0= low levels; 1= high levels), where 0 was the reference category and Obesity (0=no; 1=yes) ''Biomarker X'' was taken ...
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### Conditional probability: how do i find the conditional probability given two parameters?

It is known that 25% of full time workers are also students. It is also known that 64% of the population work full-time and that 22% of the population are students. If a member of the population is ...
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### Decomposing the effect of x on y

I have an independent variable x, and a dependent variable y which is the sum of two variables, ...
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### convergence of MSE (mean square error) using Sequential monte carlo

I am using sequential monte carlo method for a regression problem with bayesian estimation . I am trying to find a measure to confirm that my distribution has converged to the actual posterior ...
24 views

### convergence rate of Pearson correlation matrix

I posted recently a related question about the convergence rate of a Pearson correlation coefficient, here. Now, I am interested in the matrix version. Let $X_1,\ldots,X_N \sim \mathcal{N}(0,1)$ be ...
5 views

### Equivalent method to simplex algorithm in machine learning

I always use simplex algorithm for minimization problems. Is there an equivalent approach in machine learning that could possibly be better, smarter?
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### Multi-tier classification

First of all, I'm not sure wether the question title is correct, but I'm facing a puzzling problem. Please point me to the correct term and some relevant literature. This is the problem: Let's say I ...
66 views

### Structuring Many-Factor Data for Linear Regression in R

I have a fairly large dataset of the following form, and I want to run a linear regression returning coefficients for each factor: ...
23 views

### Terminology confusion re: sample outcomes

I've just started Wasserman's All of Statistics and he starts by saying: "The sample space $\Omega$, is the set of possible outcomes of an experiment. Points $\omega$ in $\Omega$ are called sample ...
10 views

### Change in lasso coefficients when subset of the feature set is used

Model 1 : Suppose I have a feature set {feature 1,feature 2,feature 3, feature 4} and a target, and I use lasso regression to build a predictive model. Now suppose feature 1,2,4 got non-zero ...
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### Difference Between Discrete Time Proportional Hazards and Logistic Regression

My data consists of one row per person, per month that person was "exposed" to an event. So the month is the discrete time and the row corresponds to one "person-month". There are a few independent ...
59 views

### Example of heavy-tailed distribution that is not long-tailed

From readings about heavy-, and long-tailed distributions, I understood that all long-tailed distributions are heavy-tailed, but not all heavy-tailed distributions are long-tailed. Could somebody ...
16 views

### What is it called when the Test Set and Training set is the same?

Normally when evaluating a model, the training data is split into a test set and a training set. I want to evaluate the best possible performance of the classifier on my task. So I have Trained it ...
28 views

### Data Transformation with many 0 and 1

I'd like to transform my data (many 0 and 1) to reach normal Distribution. Is there a way to transform the following Distribution?
29 views

### Fisher Projection vs Linear Discriminant Analysis [on hold]

Basically, I am confused between Fisher and LDA. Looking for differences between the two. How is the Fischer projection computed in R?
8 views

### future prediction by inverting GAM model coefficients [on hold]

I am new to R. I am trying to fit GLM and GAM model to my species data against few variables, which I have already done using GLM and mgcv package (GAM). I got some parametric coefficients. The next ...
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### Comparing adjacency matrices

I have 25 weighted adjacency matrices which can be potentially translate into 25 networks. I want to see how similar'' are the resulting networks (in a graph theory sense). Is there a way to do ...
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### coefficents estimators via “stepAIC” and “Lasso-penalization”

i hope you can help me out with this one. First I split up my data set into a training and test data set. Then I used two approaches to build a logistic regression model. The first one was via ...
21 views

### least square mean

Here I read that when comparing groups with different characteristics (age, percentage of males, body mass index) means should be corrected for such imbalances. These corrected means are called ...
62 views

### Why is MCMC needed when estimating a parameter using MAP

Given the formula for MAP estimation of a parameter Why is a MCMC (or similar) approach needed, couldn't I just take the derivative, set it to zero and then solve for the parameter?
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### REgression analysis when both dependent and independent variables are on likert scale

My questionnaires have recently been filled but am yet to figure out how to analyze my data. My topic is "impact of electronic banking on customer value and loyalty". Thus my dependent variable is ...
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### sapply with function using multiple columns as input [migrated]

I have a data frame with let's say 2 columns and 4 rows (it's bigger... I am just making it simpler) like this: Value: 0.2, 0.3, 0.5, 0.8 R: 1, 0, 1, 0 I m trying to write a sapply line that given ...
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### What statistical analysis should I use for this (attached) dataset?

I have a dataset of 815 positive examples and 9492 negative examples for a certain class. Each example is represented by 12 features and a target label (i.e. TRUE/FALSE). The dataset is in a CSV file ...
15 views

### Deriving expectation involving Wishart distributions $E[\bf{A(A'WA)^-A'W}]=\bf{A(A'\Sigma A)^-A'\Sigma}$

I have a problem deriving two expectation involving Wishart distributions with mean zero. Let $\bf{W} \sim {W_p}({\bf{\Sigma }},$$n\bf{)} and \bf{A}$$: p\times q$. Prove that ...
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### error R in Crossvalidation (fold-3) and RR-BLUP and compare GBLUP [on hold]

Crossvalidation three sets of genomic evaluation methods (fold-3) and two   RR-BLUP and compare GBLUP we run the following command in the program R; 1-Sincerely, with thanks, the other two that I need ...
75 views

### Question about the answer to “Local polynomial regression: Why does the variance increase monotonically in the degree?”

I appreciated Marco's elegant answer explaining why the variance of a local polynomial regression increases monotonically in the degree. However, in the end of the proof, I find difficult to calculate ...
25 views

### How do we interpret the parameters of a nls regression model? [on hold]

The data for these results are from two different seasons (A & B). Please explain with regards to the parameters (a,FRE & FGPP) in the model. FREE and FGPP are also response variables. NEE ...
36 views

### How much variation should a clustering algorithm explain?

When running a cluster analysis, the algorithm used normally returns a measure of how much variation the clustering explains. e.g. "This clustering explains 96 % of the variation in the data" ...
15 views

### Partial derivatives of the log-likelihood cost function with softmax layers

I am using Bishop's book and this online book to study neural nets. The log likelihood cost function $E = -\sum_{n}\sum_{k=1}^{C}t_{k}^{n}\ln \frac{y_{k}(\boldsymbol{x}^{n})}{t_{k}^{n}}$ , where the ...
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### Panel estimation - all variables required to be stationary?

I am using fixed and Tobit estimator using panel data. As a result of the panel stationary test, one of the independent variables seems to have a unit root though its first difference is stationary. I ...
42 views

### Word frequency in a vector [on hold]

I have a vector file with 1000 values. All the values were generated using Random function between 0-1. ...
13 views

### Significance Testing on total vs subgroup [on hold]

Looking for some clarification. I'm fairly new to Statistics and am using IBM Survey Reporter. Am I right in saying that the system does not run significance including total sample column, and only ...
31 views

### How could calculate sampling size for 95% confidence in a unique distribution?

I made a big list of words that I claimed more than x% of them have dictation error. For showing my confidence of claim I need to show a sample(random) that prove it(because I can survey a sample list ...
21 views

### sentiment analysis using convolutional neural networks

I was trying to modify YoonKim's code for sentiment analysis using CNN's. He applies three filters of heights=[3,4,5] and ...
13 views

### Is RMSEA an absolute or relative fit statistics test?

I've been studying Structural Equation Model and I have a doubt about RMSEA. In the book Principles and Practices of Structural Equation Modeling Kline treats RMSEA as an approximate fit index (p. ...