Edward Malthouse
Edward Malthouse
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Відео

8 Introduction to Migration model for lifetime value
Переглядів 3082 роки тому
This shows how to use Markov Chains to estimate customer lifetime value, called the migration model
10 Migration model lifetime value applications part 2
Переглядів 4042 роки тому
More examples of how to apply the migration (Markov chain) model for customer lifetime value
9 Migration model lifetime value applications part 1
Переглядів 2132 роки тому
Examples of how to apply the migration model (Markov chain) for estimating customer lifetime value
7 Discrete time survival model for customer lifetime value
Переглядів 1,3 тис.2 роки тому
I show how to estimate retention rates for customer lifetime value using the discrete time survival model
6 General retention model for lifetime value with stratification in R
Переглядів 2702 роки тому
I show how to use R to estimate retention rates for lifetime value
3. General retention model (GRM) for lifetime value
Переглядів 2802 роки тому
This defines the general retention model (GRM) for customer lifetime value (CLV). I show how to compute CLV using Excel if the retention probabilities are provided.
5. Kaplan-Meier estimate of retention rates for general retention model of lifetime value
Переглядів 4392 роки тому
This covers the Kaplan Meier estimate of survival probabilities and applies them to estimating customer lifetime value.
4. Simple retention model (SRM) for lifetime value in Excel
Переглядів 2372 роки тому
This shows how to compute the PDF, expected value and lifetime value by "brute force" in Excel, as well as with the formulas derived in my other video.
2. Simple retention model for lifetime value
Переглядів 3372 роки тому
This covers the simple retention model for estimating customer lifetime value (CLV). I discuss the assumptions, show how to compute the expected time until cancelation and the lifetime value with or without payments at time 0.
1. Intro to customer lifetime value (CLV)
Переглядів 4922 роки тому
Introduces the concepts of customer profitability, customer lifetime value, prospect lifetime value, customer equity for customer evaluation
5 Picking number of clusters, profiling
Переглядів 7933 роки тому
This video discusses different ways of selecting the number of clusters including using the objective function value, pseudo F, silhouette statistics and managerial implications. I show how to profile clusters using one-way ANOVA and the chi-square test of independence.
9. Latent class analysis
Переглядів 7513 роки тому
This introduces the latent class model
8. Gaussian mixture model part 2
Переглядів 3293 роки тому
Bivariate and multi-variate Gaussian mixture model in R and python
7. GMM part 1
Переглядів 3593 роки тому
Introduction to Gaussian mixture models. This covers the basic distributions: class-conditional, prior, posterior, observed. I show to estimate it in R and Python.
6 Breaking K means and algorithms
Переглядів 2413 роки тому
6 Breaking K means and algorithms
3 Running K means in R
Переглядів 2813 роки тому
3 Running K means in R
4 Cluster analysis steps
Переглядів 7743 роки тому
4 Cluster analysis steps
2 One way ANOVA review for cluster analyssi
Переглядів 8063 роки тому
2 One way ANOVA review for cluster analyssi
1 Intro to clustering
Переглядів 3423 роки тому
1 Intro to clustering
Introduction to dimension reduction recommender systems
Переглядів 1253 роки тому
Introduction to dimension reduction recommender systems
Introduction to latent variables
Переглядів 1,9 тис.3 роки тому
Introduction to latent variables
Principal curves
Переглядів 1 тис.3 роки тому
Principal curves
PCA examples
Переглядів 6373 роки тому
PCA examples
5 4 Koyck Intervention
Переглядів 813 роки тому
5 4 Koyck Intervention
5 2 lags and Koyck
Переглядів 2493 роки тому
5 2 lags and Koyck
5 5 introduction to vector autoregression models
Переглядів 2533 роки тому
5 5 introduction to vector autoregression models
5 3 Causality and Quasi experimental designs
Переглядів 1253 роки тому
5 3 Causality and Quasi experimental designs
5 1 Introduction to Dynamic Regression
Переглядів 1,3 тис.3 роки тому
5 1 Introduction to Dynamic Regression
4 2 ARIMA Autoregressive models
Переглядів 2763 роки тому
4 2 ARIMA Autoregressive models

КОМЕНТАРІ

  • @mayank4873
    @mayank4873 2 місяці тому

    your lecture is so awesome please upload more videos 🤩😌

  • @mayank4873
    @mayank4873 2 місяці тому

    awesomee 🤩

  • @mayank4873
    @mayank4873 3 місяці тому

    awesome🤩

  • @AnonymousDAT-oh5vi
    @AnonymousDAT-oh5vi 5 місяців тому

    Thank you for such detailed explanation. Gonna explore all of your time series videos now.

  • @Bksemsem
    @Bksemsem 5 місяців тому

    This should get more views ! Thanks alot !

  • @sanafarahani6472
    @sanafarahani6472 5 місяців тому

    Thank you! i was looking for a solution abbout how to calcualte the second moment. you explained well.

  • @justsomegirlwithoutamustac5837
    @justsomegirlwithoutamustac5837 6 місяців тому

    YOU'RE THE BEST TEACHER IVE EVER MET THANJ YOU SO MUCH FOR YOUR VIDEO <3

  • @happygrace8065
    @happygrace8065 9 місяців тому

    Thank you Sir

  • @Bksemsem
    @Bksemsem Рік тому

    This is by far the best explanations for such a topic on youtube. You really have my uttermost respect and gratitude.

  • @Durgeshkumar-mn5lt
    @Durgeshkumar-mn5lt Рік тому

    great sir , thanks alot

  • @aundo1647
    @aundo1647 Рік тому

    great teaching style, thank you!

  • @basharmohammad5353
    @basharmohammad5353 Рік тому

    Thanks a lot

  • @changdali1330
    @changdali1330 Рік тому

    Incredibly clear. Your interpretation is way better than my professor's! Thank you, sir.

  • @jiaqint961
    @jiaqint961 Рік тому

    Thank you for all your videos!

  • @includestdio.h8492
    @includestdio.h8492 Рік тому

    >return("thank you professor")

  • @peikspencer9422
    @peikspencer9422 Рік тому

    I typed out the function manually if anyone wants it freqdist=function(x, freqorder=F) { Counts=table(x) n=sum(counts) if (freqorder) ord=order(-counts) else ord+1:length(counts) data.frame( row.names=row.name(counts[ord]), Counts=as.vector(counts[ord]), Percent=100*as.vector(counts[ord])/n, CumCount=cumsum(as.vector(counts[ord])), CumpPercent=100*cumsum(as.vector(counts[ord]))/n ) } Some formatting will of course be needed.

  • @tracyyang1832
    @tracyyang1832 Рік тому

    Can you provide the link for this amazon data?

  • @tracyyang1832
    @tracyyang1832 Рік тому

    This series of videos are really great! Thank you so much. Wondering is it possible to upload the video notes here?

  • @farelinho6576
    @farelinho6576 Рік тому

    I love u

  • @RobertChen-qv5gz
    @RobertChen-qv5gz Рік тому

    perhaps women are richer than men

  • @yt-1161
    @yt-1161 Рік тому

    @12:00 so just because the y-distance from the intersection point to x2 is longer, the probability that it came from class 2 is higher ? I see that Posterior is direct proportional to conditional to class conditional distribution times prior, so it would also depend on prior, am I wrong ?

  • @alessandrorosati969
    @alessandrorosati969 Рік тому

    How can you do misclassification in mclust when there is a noise ?

  • @yt-1161
    @yt-1161 Рік тому

    What kind of script is that ?

  • @yt-1161
    @yt-1161 Рік тому

    @1:08 when you refer to "last week" which video is that ? There's no playlist for this subject. Your lectures are very good but in a random order

  • @alishermirmanov5608
    @alishermirmanov5608 Рік тому

    Thanks!!

  • @henrikswedish378
    @henrikswedish378 Рік тому

    This is what UA-cam should be used for. Very clear and easy to follow. Thank you

  • @thomasjefferson6225
    @thomasjefferson6225 Рік тому

    Is there any way I could get your pdf that youre presenting off of? Quality material. '

  • @wenfanghu3724
    @wenfanghu3724 Рік тому

    Really like your way of teaching! I learned a lot from watching your series of videos. Thank you!

  • @Pooh991
    @Pooh991 Рік тому

    Excelent video, professor. Really thorough explanation. Thank you for sharing this.

  • @Martyr022
    @Martyr022 Рік тому

    is there any way we can get the PDF copy of these notes?

  • @onpointux
    @onpointux Рік тому

    Very good, will be consuming a lot more videos from your channel. Thanks so much!

  • @Henry4pf
    @Henry4pf Рік тому

    🐐🐐

  • @yuanqixue9194
    @yuanqixue9194 Рік тому

    Very helpful! The best video on this topic.

  • @mkd4524
    @mkd4524 Рік тому

    much clear explanation than my prof

  • @kierballar4218
    @kierballar4218 Рік тому

    thank you :)

  • @fullpowersuperperfectcell3799

    Wow! This is fantastic. I want to thank you for helping me with my frequency distribution graph.

  • @kevinfine5181
    @kevinfine5181 Рік тому

    this video was actually amazing. I haven't understood stats for the two years of uni, now in my third and watching this video actually clicked everything together for me. I usually don't comment on stuff but just wanted to show my appreciation for your help. thank you so much!

  • @AJ-et3vf
    @AJ-et3vf Рік тому

    awesome video sir. thank you

  • @rafaelmello3823
    @rafaelmello3823 2 роки тому

    Thanks so much for these series of video, It has been so helpful!

  • @stat1726
    @stat1726 2 роки тому

    Very good interpretation.. indeed

  • @stat1726
    @stat1726 2 роки тому

    Thanks.. now lot of concepts u made clear.

  • @nganja2251
    @nganja2251 2 роки тому

    nice video, but can the frequency of each variable be increase in a frequency table ?

  • @thebjjtroll6778
    @thebjjtroll6778 2 роки тому

    This is the best explanation on all of UA-cam! you bring together the Maths, the intuition, derivations and illustrations. Thank you so much !

  • @gaibiii1806
    @gaibiii1806 2 роки тому

    great

  • @me-hn4bs
    @me-hn4bs 2 роки тому

    please I have some questions the first question is do we start by first differences or seasonal differences the second question is how to write the formula when the difference is > 1 because that B will change the third question is what is the formula for additive model

  • @jiaqianliu6593
    @jiaqianliu6593 2 роки тому

    very clear!

  • @Saijana
    @Saijana 2 роки тому

    Really great explanation... Almost makes me reconsider dropping my statistics minor.

  • @gaibiii1806
    @gaibiii1806 2 роки тому

    helpful thanks

  • @gaibiii1806
    @gaibiii1806 2 роки тому

    helpful

  • @miguelpena7726
    @miguelpena7726 2 роки тому

    Thank you very much for this interesting video!